Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc.
License: Apache License 2.0
I get the following error when running the Embedding Pipeline in the 1_build_image_search_engine.ipynb notebook
TypeError: cannot pickle '_thread.lock' object
TypeError Traceback (most recent call last)
Cell In[3], line 18
11 yield item
13 # Embedding pipeline
14 p_embed = (
15 pipe.input('src')
16 .flat_map('src', 'img_path', load_image)
17 .map('img_path', 'img', ops.image_decode())
---> 18 .map('img', 'vec', ops.image_embedding.timm(model_name=MODEL, device=DEVICE))
19 )
File /anaconda/envs/azureml_py310_sdkv2/lib/python3.10/site-packages/towhee/runtime/pipeline.py:143, in Pipeline.map(self, input_schema, output_schema, fn, config)
141 uid = uuid.uuid4().hex
142 fn_action = self._to_action(fn)
--> 143 dag_dict = deepcopy(self._dag)
144 dag_dict[uid] = {
145 'inputs': input_schema,
146 'outputs': output_schema,
(...)
153 'next_nodes': [],
154 }
155 dag_dict[self._clo_node]['next_nodes'].append(uid)
File /anaconda/envs/azureml_py310_sdkv2/lib/python3.10/copy.py:146, in deepcopy(x, memo, _nil)
...
--> 161 rv = reductor(4)
162 else:
163 reductor = getattr(x, "reduce", None)
TypeError: cannot pickle '_thread.lock' object
I think there needs to be a description or a way to install it
import time
import towhee
# Please note the first time run will take time to download model and other files.
start = time.time()
collection = create_milvus_collection('x3d_m', 2048)
dc = (
towhee.read_csv('reverse_video_search.csv')
.runas_op['id', 'id'](func=lambda x: int(x))
.video_decode.ffmpeg['path', 'frames'](sample_type='uniform_temporal_subsample', args={'num_samples': 16})
.action_classification['frames', ('labels', 'scores', 'features')].pytorchvideo(
model_name='x3d_m', skip_preprocess=True)
.to_milvus['id', 'features'](collection=collection, batch=10)
)
end = time.time()
print('Total insert time: %.2fs'%(end-start))
print('Total number of inserted data is {}.'.format(collection.num_entities))
I try to run the "video/deepfake_detection/1_deepfake_detection.ipynb"with the following code:
from towhee import ops, pipe, DataCollection
p = (
pipe.input('path')
.map('path', 'scores', ops.towhee.deepfake())
.output('scores')
# .output('path')
)
DataCollection(p('./train/deepfake_video/aejgdsuoqg.mp4')).show()
,but an error happend:
the filepath is correct,is there anything wrong with the code?
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb 单元格 1 in 4
[1](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb#W0sdnNjb2RlLXJlbW90ZQ%3D%3D?line=0) from towhee import ops, pipe, DataCollection
[3](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb#W0sdnNjb2RlLXJlbW90ZQ%3D%3D?line=2) p = (
----> [4](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb#W0sdnNjb2RlLXJlbW90ZQ%3D%3D?line=3) pipe.input('path')
[5](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb#W0sdnNjb2RlLXJlbW90ZQ%3D%3D?line=4) .map('path', 'scores', ops.towhee.deepfake())
[6](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb#W0sdnNjb2RlLXJlbW90ZQ%3D%3D?line=5) .output('scores')
[7](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb#W0sdnNjb2RlLXJlbW90ZQ%3D%3D?line=6) # .output('path')
[8](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb#W0sdnNjb2RlLXJlbW90ZQ%3D%3D?line=7) )
[10](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/image/reverse_image_search/2_deep_dive_image_search.ipynb#W0sdnNjb2RlLXJlbW90ZQ%3D%3D?line=9) DataCollection(p('[./train/deepfake_video/aejgdsuoqg.mp4](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a2253485445435f646576656c6f70227d.vscode-resource.vscode-cdn.net/home/image_check/code/examples/image/reverse_image_search/train/deepfake_video/aejgdsuoqg.mp4)')).show()
File [~/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/pipeline.py:116](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a2253485445435f646576656c6f70227d.vscode-resource.vscode-cdn.net/home/image_check/code/examples/image/reverse_image_search/~/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/pipeline.py:116), in Pipeline.output(self, *output_schema, **config_kws)
113 dag_dict[self._clo_node]['next_nodes'].append(uid)
115 run_pipe = RuntimePipeline(dag_dict, config=config_kws)
--> 116 run_pipe.preload()
117 return run_pipe
File [~/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/runtime_pipeline.py:140](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a2253485445435f646576656c6f70227d.vscode-resource.vscode-cdn.net/home/image_check/code/examples/image/reverse_image_search/~/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/runtime_pipeline.py:140), in RuntimePipeline.preload(self)
136 def preload(self):
137 """
138 Preload the operators.
139 """
--> 140 return _Graph(self._dag_repr.nodes, self._dag_repr.edges, self._operator_pool, self._thread_pool)
...
File "/home/image_check/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/operator_manager/operator_loader.py", line 59, in _load_legacy_op
module = importlib.util.module_from_spec(spec)
File "", line 553, in module_from_spec
AttributeError: 'NoneType' object has no attribute 'loader'
Output is truncated. View as a [scrollable element](command:cellOutput.enableScrolling?9cfee1bc-701f-405f-9006-130d95f68b21) or open in a [text editor](command:workbench.action.openLargeOutput?9cfee1bc-701f-405f-9006-130d95f68b21). Adjust cell output [settings](command:workbench.action.openSettings?%5B%22%40tag%3AnotebookOutputLayout%22%5D)...
Many thanks!
image_embedding.timm(model_name='resnet50')在某些环境下无法连接，我想是否能设置加载本地模型如
image_embedding.timm(path='modelpath',model_name='resnet50')
How to get or print the similarity score using 1_build_image_search_engine.ipynb
How to save and load the model in towhee because sometimes we already have the model and want to use that one?
I am trying to replicate/run this (under 1_build_question_answering_engine.ipynb cell 5):
insert_pipe = (
pipe.input('id', 'question', 'answer')
.map('question', 'vec', ops.text_embedding.dpr(model_name='facebook/dpr-ctx_encoder-single-nq-base'))
.map('vec', 'vec', lambda x: x / np.linalg.norm(x, axis=0))
.map(('id', 'vec'), 'insert_status', ops.ann_insert.milvus_client(host='127.0.0.1', port='19530', collection_name='question_answer'))
.output()
)
But i keep getting the following error: 2
RuntimeError Traceback (most recent call last)
Cell In[124], line 6
1 insert_pipe = (
2 pipe.input('id', 'question', 'answer')
3 .map('question', 'vec', ops.text_embedding.dpr(model_name='facebook/dpr-ctx_encoder-single-nq-base'))
4 .map('vec', 'vec', lambda x: x / np.linalg.norm(x, axis=0))
5 .map(('id', 'vec'), 'insert_status', ops.ann_insert.milvus_client(host='127.0.0.1', port='19530', collection_name='question_answer'))
----> 6 .output()
7 )
File /opt/homebrew/lib/python3.11/site-packages/towhee/runtime/pipeline.py:101, in Pipeline.output(self, *output_schema)
98 dag_dict[self._clo_node]['next_nodes'].append(uid)
100 run_pipe = RuntimePipeline(dag_dict)
--> 101 run_pipe.preload()
102 return run_pipe
File /opt/homebrew/lib/python3.11/site-packages/towhee/runtime/runtime_pipeline.py:153, in RuntimePipeline.preload(self)
149 def preload(self):
150 """
151 Preload the operators.
152 """
--> 153 return _Graph(self._dag_repr.nodes, self._dag_repr.edges, self._operator_pool, self._thread_pool, TimeProfiler(False))
File /opt/homebrew/lib/python3.11/site-packages/towhee/runtime/runtime_pipeline.py:67, in _Graph.init(self, nodes, edges, operator_pool, thread_pool, time_profiler, trace_edges)
65 self.features = None
66 self._time_profiler.record(Event.pipe_name, Event.pipe_in)
---> 67 self._initialize()
68 self._input_queue = self._data_queues[0]
File /opt/homebrew/lib/python3.11/site-packages/towhee/runtime/runtime_pipeline.py:83, in _Graph._initialize(self)
81 node = create_node(self._nodes[name], self._operator_pool, in_queues, out_queues, self._time_profiler)
82 if not node.initialize():
---> 83 raise RuntimeError(node.err_msg)
84 self._node_runners.append(node)
RuntimeError: Node-text-embedding/dpr-0 runs failed, error msg: Create text-embedding/dpr-0 operator text-embedding/dpr:main with args None and kws {'model_name': 'facebook/dpr-ctx_encoder-single-nq-base'} failed, err:
DPRContextEncoder requires the PyTorch library but it was not found in your environment. Checkout the instructions on the
installation page: https://pytorch.org/get-started/locally/ and follow the ones that match your environment.
Please note that you may need to restart your runtime after installation.
, Traceback (most recent call last):
File "/opt/homebrew/lib/python3.11/site-packages/towhee/runtime/nodes/node.py", line 88, in initialize
self._op = self._op_pool.acquire_op(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/lib/python3.11/site-packages/towhee/runtime/operator_manager/operator_pool.py", line 106, in acquire_op
op = self._op_loader.load_operator(hub_op_id, op_args, op_kws, tag, latest)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/lib/python3.11/site-packages/towhee/runtime/operator_manager/operator_loader.py", line 154, in load_operator
op = factory(function, arg, kws, tag, latest)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/lib/python3.11/site-packages/towhee/runtime/operator_manager/operator_loader.py", line 137, in _load_operator_from_hub
return self._load_operator_from_path(path, function, arg, kws, tag)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/lib/python3.11/site-packages/towhee/runtime/operator_manager/operator_loader.py", line 125, in _load_operator_from_path
return self._instance_operator(op, arg, kws) if op is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/lib/python3.11/site-packages/towhee/runtime/operator_manager/operator_loader.py", line 163, in _instance_operator
return op(*arg, **kws) if kws is not None else op(*arg)
^^^^^^^^^^^^^^^
File "/Users/jess/.towhee/operators/text-embedding/dpr/versions/main/init.py", line 19, in dpr
return Dpr(**kwargs)
^^^^^^^^^^^^^
File "/Users/jess/.towhee/operators/text-embedding/dpr/versions/main/dpr.py", line 40, in init
raise e
File "/Users/jess/.towhee/operators/text-embedding/dpr/versions/main/dpr.py", line 37, in init
self.model = DPRContextEncoder.from_pretrained(model_name)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/lib/python3.11/site-packages/transformers/utils/import_utils.py", line 1039, in getattribute
requires_backends(cls, cls._backends)
File "/opt/homebrew/lib/python3.11/site-packages/transformers/utils/import_utils.py", line 1027, in requires_backends
raise ImportError("".join(failed))
ImportError:
DPRContextEncoder requires the PyTorch library but it was not found in your environment. Checkout the instructions on the
installation page: https://pytorch.org/get-started/locally/ and follow the ones that match your environment.
Please note that you may need to restart your runtime after installation.
I am using
towhee==1.1.1
Pydantic. == 1.10.11
ValidationError Traceback (most recent call last)
Cell In[10], line 31
19 aps.append(sum(precisions) / len(precisions))
21 return sum(aps) / len(aps)
23 eval_pipe = (
24 pipe.input('path')
25 .flat_map('path', 'path', lambda x: glob.glob(x))
26 .map('path', 'frames', ops.video_decode.ffmpeg(sample_type='uniform_temporal_subsample', args={'num_samples': 16}))
27 .map('frames', ('labels', 'scores', 'features'), ops.action_classification.pytorchvideo(model_name='x3d_m', skip_preprocess=True))
28 .map('features', 'result', ops.ann_search.milvus_client(host='127.0.0.1', port='19530', collection_name='x3d_m', limit=10))
29 .map('result', 'predict', lambda x: [i[0] for i in x])
30 .map('path', 'ground_truth', ground_truth)
---> 31 .window_all(('ground_truth', 'predict'), 'mHR', mean_hit_ratio)
32 .window_all(('ground_truth', 'predict'), 'mAP', mean_average_precision)
33 .output('mHR', 'mAP')
34 )
36 res = DataCollection(eval_pipe('./test//.mp4'))
37 res.show()
File ~/Documents/milvus/.milvusenv/lib/python3.11/site-packages/towhee/runtime/pipeline.py:348, in Pipeline.window_all(self, input_schema, output_schema, fn, config)
326 def window_all(self, input_schema, output_schema, fn, config=None) -> 'Pipeline':
327 """
328 Read all rows as single window and perform action.
329
(...)
346 [10, 14]
347 """
--> 348 output_schema = self._check_schema(output_schema)
349 input_schema = self._check_schema(input_schema)
351 uid = uuid.uuid4().hex
File ~/Documents/milvus/.milvusenv/lib/python3.11/site-packages/towhee/runtime/pipeline.py:517, in Pipeline._check_schema(schema)
515 @staticmethod
516 def _check_schema(schema):
--> 517 return TupleForm(schema_data=schema).schema_data
File ~/Documents/milvus/.milvusenv/lib/python3.11/site-packages/pydantic/main.py:341, in pydantic.main.BaseModel.init()
ValidationError: 1 validation error for TupleForm
schema_data -> 0
string does not match regex "^[a-z][a-z0-9_]$" (type=value_error.str.regex; pattern=^[a-z][a-z0-9_]$)
你好，我正在学习并尝试跟着这个示例搭建一个以图搜图的项目，我遇到了TypeError的错误。
具体是在操作到Embedding pipeline这一步时（加载图片并看到金鱼），收到了TypeError 的错误，不知道问题出在哪里，希望获得帮助，谢谢！
The following code snippet is an example provided of using the pre-trained ResNet50 model ('resnet50') to generate an image embedding:
p = ( pipe.input('path') .map('path', 'img', ops.image_decode()) .map('img', 'vec', ops.image_embedding.timm(model_name='resnet50')) .output('img', 'vec') )
But i want to use trained weights of resnet50(fine-tune) to extract embedding, How to reload the trained model weights of resnet50?
Could you please provide an example.
thanks!
Hello. When I use ''ops.image_embedding.timm(model_name='resnet50', checkpoint_path=my_checkpoint_path)'' , even if I specify the ''checkpoint_path='' to a specific model path, it still checks if the pre-trained model exists in the [ .cache] directory. If it is not present, the function automatically downloads the pre-trained model. In this case, is it actually using the model I specified in 'checkpoint_path=' ? Thanks for you!
Image Search Engine案例，最后一步Gradio报错如下：
2022-08-26 23:06:57,117 - 12779106304 - decorators.py-decorators:95 - ERROR: RPC error: [search], <MilvusException: (code=1, message=checkIfLoaded failed when search, collection:reverse_image_search_norm, partitions:[], err = showPartitions failed, collection = reverse_image_search_norm, partitionIDs = [], reason = collection 435558044005564417 has not been loaded into QueryNode)>, <Time:{'RPC start': '2022-08-26 23:06:57.105122', 'RPC error': '2022-08-26 23:06:57.117755'}>
Traceback (most recent call last):
File "/Users/borye/miniforge3/lib/python3.9/site-packages/gradio/routes.py", line 247, in run_predict
output = await app.blocks.process_api(
File "/Users/borye/miniforge3/lib/python3.9/site-packages/gradio/blocks.py", line 645, in process_api
output = self.postprocess_data(fn_index, predictions, state)
File "/Users/borye/miniforge3/lib/python3.9/site-packages/gradio/blocks.py", line 594, in postprocess_data
prediction_value = predictions[i]
TypeError: '_Reason' object is not subscriptable
RuntimeError Traceback (most recent call last)
Cell In[33], line 6
4 next(reader)
5 for row in reader:
----> 6 insert_pipe(*row)
File D:\anaconda\envs\DL\lib\site-packages\towhee\runtime\runtime_pipeline.py:149, in RuntimePipeline.call(self, *inputs)
147 if self._enable_trace:
148 self._time_profiler_list.append(graph.time_profiler)
--> 149 return graph(inputs)
File D:\anaconda\envs\DL\lib\site-packages\towhee\runtime\runtime_pipeline.py:104, in _Graph.call(self, inputs)
102 def call(self, inputs: Union[Tuple, List]):
103 f = self.async_call(inputs)
--> 104 return f.result()
File D:\anaconda\envs\DL\lib\site-packages\towhee\runtime\runtime_pipeline.py:34, in _GraphResult.result(self)
33 def result(self):
---> 34 ret = self._graph.result()
35 del self._graph
36 return ret
File D:\anaconda\envs\DL\lib\site-packages\towhee\runtime\runtime_pipeline.py:87, in _Graph.result(self)
85 errs += node.err_msg + '\n'
86 if errs:
---> 87 raise RuntimeError(errs)
88 end_edge_num = self._nodes['_output'].out_edges[0]
89 res = self._data_queues[end_edge_num]
RuntimeError: Node-ann-insert/milvus-client-2 runs failed, error msg: <DataTypeNotMatchException: (code=0, message=The data fields number is not match with schema.)>, Traceback (most recent call last):
File "D:\anaconda\envs\DL\lib\site-packages\towhee\runtime\nodes\node.py", line 156, in _call
return True, self._op(*inputs), None
File "C:\Users\Administrator.towhee\operators\ann-insert\milvus-client\versions\main\milvus_client.py", line 45, in call
mr = self._collection.insert(row)
File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\pymilvus\orm\collection.py", line 535, in insert
if not self._check_insert_data_schema(data):
File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\pymilvus\orm\collection.py", line 187, in _check_insert_data_schema
raise DataTypeNotMatchException(0, ExceptionsMessage.FieldsNumInconsistent)
pymilvus.orm.exceptions.DataTypeNotMatchException: <DataTypeNotMatchException: (code=0, message=The data fields number is not match with schema.)> pymilvus不支持VARCHAR，然后改成INT64，在导入csv文件时，出现这样的错误
run demo example abnormal.
`from towhee import pipe, ops, DataCollection
if name == 'main':
p = (
pipe.input('text')
.map('text', 'vec', ops.text_embedding.dpr(model_name='facebook/dpr-ctx_encoder-single-nq-base'))
.output('text', 'vec')
)
DataCollection(p('Hello, world.')).show()`
Traceback (most recent call last):
File "F:/Project/towhee_test/main.py", line 7, in
.output('text', 'vec')
File "E:\Anaconda3\envs\towhee_env\lib\site-packages\towhee\runtime\pipeline.py", line 103, in output
dag_dict = deepcopy(self._dag)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 241, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 241, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 241, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 281, in _reconstruct
state = deepcopy(state, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 150, in deepcopy
y = copier(x, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 241, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "E:\Anaconda3\envs\towhee_env\lib\copy.py", line 169, in deepcopy
rv = reductor(4)
TypeError: can't pickle _thread.lock objects
Process finished with exit code 1
run this file "1_text_video_retrieval_engine.ipynb" get the error:
AttributeError: module 'towhee' has no attribute 'glob'.
And this issue towhee-io/towhee#2504 can not help me,why not give the correct version,it makes users hard to execute scucess.
Hi there,
When I clone and tried to run the project "text_image_search"(branch is main), an error occurred during the step "Load Image Embeddings into Milvus". The error is shown in the screenshot below:
p.s. I am using milvus 2.0.2, and pymilvus is 2.0.2. Also using towhee 0.9.0.
(please forgive my poor english :)
I am building the Audio Image Fingerprint example and working through the file audio_fingerprint_beginner.ipynb. In that file, the code creates a Milvus collection. It appears that it is creating an empty collection (I cannot see any reference to the preloaded audio data in the call to construct the Collection).
It then goes on to create an index on this collection, as shown in the code fragment below. However, the call to collection.create_index(...) takes forever (days) on my Macbook M1. Is this expected? Am I missing something obvious (I am new to Milvus and Towhee).
I am also including a snippet of the log output of the Milvus docker container, maybe this can help . . . .
Thanks very much for any help that you can provide!
# Create Milvus collection
fields = [
FieldSchema(name='id', dtype=DataType.INT64, description='embedding ids', is_primary=True, auto_id=True),
FieldSchema(name='embedding', dtype=DataType.FLOAT_VECTOR, description='audio embeddings', dim=DIM),
FieldSchema(name='path', dtype=DataType.VARCHAR, description='audio path', max_length=500)
]
schema = CollectionSchema(fields=fields, description='audio fingerprints')
if utility.has_collection(COLLECTION_NAME):
collection = Collection(COLLECTION_NAME)
collection.drop() # drop collection if it exists
collection = Collection(name=COLLECTION_NAME, schema=schema)
# Create index
index_params = {
'metric_type': METRIC_TYPE,
'index_type': INDEX_TYPE,
'params':{"nlist":2048}
}
# the following line takes forever to run
status = collection.create_index(field_name='embedding', index_params=index_params)
Here is what Milvus is logging as create_index runs:
...
milvus-standalone | [2023/04/26 12:33:40.211 +00:00] [DEBUG] [proxy/impl.go:1742] ["DescribeIndex received"] [traceID=66b3ef4224d23663] [role=proxy] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:40.219 +00:00] [DEBUG] [allocator/id.go:140] ["IDAllocator pickCanDoFunc"] [need=1] [total=199985] [remainReqCnt=0]
milvus-standalone | [2023/04/26 12:33:40.220 +00:00] [DEBUG] [proxy/impl.go:1773] ["DescribeIndex enqueued"] [traceID=66b3ef4224d23663] [role=proxy] [MsgID=441060534750543888] [BeginTs=441060535878025217] [EndTs=441060535878025217] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:40.224 +00:00] [DEBUG] [rootcoord/root_coord.go:1880] [DescribeIndex] [role=rootcoord] ["collection name"=nnfp] ["field name"=] [msgID=441060534750543888]
milvus-standalone | [2023/04/26 12:33:40.228 +00:00] [DEBUG] [rootcoord/root_coord.go:1905] ["DescribeIndex success"] [role=rootcoord] ["collection name"=nnfp] ["field name"=] ["index names"="[_default_idx]"] [msgID=441060534750543888]
milvus-standalone | [2023/04/26 12:33:40.231 +00:00] [DEBUG] [proxy/impl.go:1816] ["DescribeIndex done"] [traceID=66b3ef4224d23663] [role=proxy] [MsgID=441060534750543888] [BeginTs=441060535878025217] [EndTs=441060535878025217] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:40.747 +00:00] [DEBUG] [proxy/impl.go:1742] ["DescribeIndex received"] [traceID=2fa65ff3f830ddf6] [role=proxy] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:40.751 +00:00] [DEBUG] [allocator/id.go:140] ["IDAllocator pickCanDoFunc"] [need=1] [total=199984] [remainReqCnt=0]
milvus-standalone | [2023/04/26 12:33:40.751 +00:00] [DEBUG] [proxy/impl.go:1773] ["DescribeIndex enqueued"] [traceID=2fa65ff3f830ddf6] [role=proxy] [MsgID=441060534750543889] [BeginTs=441060536022466562] [EndTs=441060536022466562] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:40.754 +00:00] [DEBUG] [rootcoord/root_coord.go:1880] [DescribeIndex] [role=rootcoord] ["collection name"=nnfp] ["field name"=] [msgID=441060534750543889]
milvus-standalone | [2023/04/26 12:33:40.754 +00:00] [DEBUG] [rootcoord/root_coord.go:1905] ["DescribeIndex success"] [role=rootcoord] ["collection name"=nnfp] ["field name"=] ["index names"="[_default_idx]"] [msgID=441060534750543889]
milvus-standalone | [2023/04/26 12:33:40.756 +00:00] [DEBUG] [proxy/impl.go:1816] ["DescribeIndex done"] [traceID=2fa65ff3f830ddf6] [role=proxy] [MsgID=441060534750543889] [BeginTs=441060536022466562] [EndTs=441060536022466562] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:41.270 +00:00] [DEBUG] [proxy/impl.go:1742] ["DescribeIndex received"] [traceID=145563f16f72ffad] [role=proxy] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:41.274 +00:00] [DEBUG] [allocator/id.go:140] ["IDAllocator pickCanDoFunc"] [need=1] [total=199983] [remainReqCnt=0]
milvus-standalone | [2023/04/26 12:33:41.275 +00:00] [DEBUG] [proxy/impl.go:1773] ["DescribeIndex enqueued"] [traceID=145563f16f72ffad] [role=proxy] [MsgID=441060534750543890] [BeginTs=441060536153276418] [EndTs=441060536153276418] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:41.278 +00:00] [DEBUG] [rootcoord/root_coord.go:1880] [DescribeIndex] [role=rootcoord] ["collection name"=nnfp] ["field name"=] [msgID=441060534750543890]
milvus-standalone | [2023/04/26 12:33:41.279 +00:00] [DEBUG] [rootcoord/root_coord.go:1905] ["DescribeIndex success"] [role=rootcoord] ["collection name"=nnfp] ["field name"=] ["index names"="[_default_idx]"] [msgID=441060534750543890]
milvus-standalone | [2023/04/26 12:33:41.281 +00:00] [DEBUG] [proxy/impl.go:1816] ["DescribeIndex done"] [traceID=145563f16f72ffad] [role=proxy] [MsgID=441060534750543890] [BeginTs=441060536153276418] [EndTs=441060536153276418] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:41.805 +00:00] [DEBUG] [proxy/impl.go:1742] ["DescribeIndex received"] [traceID=7684d69bea24aba4] [role=proxy] [db=] [collection=nnfp] [field=] ["index name"=]
milvus-standalone | [2023/04/26 12:33:41.815 +00:00] [DEBUG] [allocator/id.go:140] ["IDAllocator pickCanDoFunc"] [need=1] [total=199982] [remainReqCnt=0]
milvus-standalone | [2023/04/26 12:33:41.816 +00:00] [DEBUG] [proxy/impl.go:1773] ["DescribeIndex enqueued"] [traceID=7684d69bea24aba4] [role=proxy] [MsgID=441060534750543891] [BeginTs=441060536299552769] [EndTs=441060536299552769] [db=] [collection=nnfp] [field=] ["index name"=]
...
p = (
pipe.input('path')
.map('path', 'img', ops.image_decode.cv2('rgb'))
.map('img', 'vec', ops.image_text_embedding.clip(model_name='clip_vit_base_patch16', modality='image'))
.map('vec', 'vec', lambda x: x / np.linalg.norm(x))
.output('img', 'vec')
)
DataCollection(p('./teddy.png')).show()
Towhee version: 0.9.1.dev111
Downloading https://towhee.io/image-text-embedding/clip/resolve/branch/main/README.md to /Users/jn/.towhee/operators/image-text-embedding/clip/files: 100%|██████████| 5.20k/5.20k [00:00<00:00, 968kB/s]
Downloading https://towhee.io/image-text-embedding/clip/resolve/branch/main/tabular2.png to /Users/jn/.towhee/operators/image-text-embedding/clip/files: 100%|██████████| 22.9k/22.9k [00:00<00:00, 3.03MB/s]
Downloading https://towhee.io/image-text-embedding/clip/resolve/branch/main/tabular1.png to /Users/jn/.towhee/operators/image-text-embedding/clip/files: 100%|██████████| 189k/189k [00:00<00:00, 1.45MB/s]
Downloading https://towhee.io/image-text-embedding/clip/resolve/branch/main/vec1.png to /Users/jn/.towhee/operators/image-text-embedding/clip/files: 100%|██████████| 13.3k/13.3k [00:00<00:00, 793kB/s]
2023-05-11 03:21:10,276 - 4730060288 - operator_loader.py-operator_loader:131 - ERROR: HTTPSConnectionPool(host='towhee.io', port=443): Max retries exceeded with url: /image-text-embedding/clip/resolve/branch/main/.gitattributes (Caused by SSLError(SSLEOFError(8, 'EOF occurred in violation of protocol (_ssl.c:1129)'))), Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/urllib3/connectionpool.py", line 700, in urlopen
self._prepare_proxy(conn)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/urllib3/connectionpool.py", line 996, in _prepare_proxy
conn.connect()
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/urllib3/connection.py", line 419, in connect
self.sock = ssl_wrap_socket(
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/urllib3/util/ssl_.py", line 449, in ssl_wrap_socket
ssl_sock = _ssl_wrap_socket_impl(
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/urllib3/util/ssl_.py", line 493, in _ssl_wrap_socket_impl
return ssl_context.wrap_socket(sock, server_hostname=server_hostname)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/ssl.py", line 500, in wrap_socket
return self.sslsocket_class._create(
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/ssl.py", line 1040, in _create
self.do_handshake()
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/ssl.py", line 1309, in do_handshake
self._sslobj.do_handshake()
ssl.SSLEOFError: EOF occurred in violation of protocol (_ssl.c:1129)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/requests/adapters.py", line 489, in send
resp = conn.urlopen(
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/urllib3/connectionpool.py", line 787, in urlopen
retries = retries.increment(
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/urllib3/util/retry.py", line 592, in increment
raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='towhee.io', port=443): Max retries exceeded with url: /image-text-embedding/clip/resolve/branch/main/.gitattributes (Caused by SSLError(SSLEOFError(8, 'EOF occurred in violation of protocol (_ssl.c:1129)')))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/operator_manager/operator_loader.py", line 128, in _load_operator_from_hub
path = get_operator(operator=function, tag=tag, latest=latest)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/hub/init.py", line 23, in get_operator
return _CACHE_MANAGER.get_operator(operator, tag, install_reqs, latest)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/hub/cache_manager.py", line 97, in get_operator
download_operator(author, repo, tag, download_path, install_reqs, latest)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/hub/downloader.py", line 171, in download_operator
_Downloader(fs).download()
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/hub/downloader.py", line 158, in download
_ = [i.result() for i in futures]
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/hub/downloader.py", line 158, in
_ = [i.result() for i in futures]
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/concurrent/futures/_base.py", line 445, in result
return self.__get_result()
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/concurrent/futures/_base.py", line 390, in __get_result
raise self._exception
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/concurrent/futures/thread.py", line 52, in run
result = self.fn(*self.args, **self.kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/hub/downloader.py", line 136, in download_url_to_file
with requests.get(url, stream=True) as r:
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/requests/api.py", line 73, in get
return request("get", url, params=params, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/requests/api.py", line 59, in request
return session.request(method=method, url=url, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/requests/sessions.py", line 587, in request
resp = self.send(prep, **send_kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/requests/sessions.py", line 701, in send
r = adapter.send(request, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/requests/adapters.py", line 563, in send
raise SSLError(e, request=request)
requests.exceptions.SSLError: HTTPSConnectionPool(host='towhee.io', port=443): Max retries exceeded with url: /image-text-embedding/clip/resolve/branch/main/.gitattributes (Caused by SSLError(SSLEOFError(8, 'EOF occurred in violation of protocol (_ssl.c:1129)')))
RuntimeError Traceback (most recent call last)
Cell In[6], line 2
1 p = (
----> 2 pipe.input('path')
3 .map('path', 'img', ops.image_decode.cv2('rgb'))
4 .map('img', 'vec', ops.image_text_embedding.clip(model_name='clip_vit_base_patch16', modality='image'))
5 .map('vec', 'vec', lambda x: x / np.linalg.norm(x))
6 .output('img', 'vec')
7 )
9 DataCollection(p('./teddy.png')).show()
File /Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/pipeline.py:101, in Pipeline.output(self, *output_schema)
98 dag_dict[self._clo_node]['next_nodes'].append(uid)
100 run_pipe = RuntimePipeline(dag_dict)
--> 101 run_pipe.preload()
102 return run_pipe
File /Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/runtime_pipeline.py:147, in RuntimePipeline.preload(self)
143 def preload(self):
144 """
145 Preload the operators.
146 """
--> 147 return _Graph(self._dag_repr.nodes, self._dag_repr.edges, self._operator_pool, self._thread_pool, TimeProfiler(False))
File /Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/runtime_pipeline.py:65, in _Graph.init(self, nodes, edges, operator_pool, thread_pool, time_profiler, trace_edges)
63 self.features = None
64 self._time_profiler.record(Event.pipe_name, Event.pipe_in)
---> 65 self.initialize()
66 self._input_queue = self._data_queues[0]
File /Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/runtime_pipeline.py:81, in _Graph.initialize(self)
79 node = create_node(self._nodes[name], self._operator_pool, in_queues, out_queues, self._time_profiler)
80 if not node.initialize():
---> 81 raise RuntimeError(node.err_msg)
82 self._node_runners.append(node)
RuntimeError: Node-image-text-embedding/clip-1 runs failed, error msg: Create image-text-embedding/clip-1 operator image-text-embedding/clip:main with args None and kws {'model_name': 'clip_vit_base_patch16', 'modality': 'image'} failed, err: Load operator failed, Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/nodes/node.py", line 88, in initialize
self._op = self._op_pool.acquire_op(
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/operator_manager/operator_pool.py", line 101, in acquire_op
op = self._op_loader.load_operator(hub_op_id, op_args, op_kws, tag, latest)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/operator_manager/operator_loader.py", line 155, in load_operator
raise RuntimeError('Load operator failed')
RuntimeError: Load operator failed
I can't understand what the result of the picture is saying.
Environment:
Current Behavior:
When I run the default example whitch is located in "examples/image/reverse_image_search/1_build_image_search_engine.ipynb", it throws an exception
https://user-images.githubusercontent.com/6244724/240831658-2a5a480c-932d-4c59-b9be-fb22dfdb82b6.png
how to solve this problem about the default towhee example ?
from pymilvus import connections, FieldSchema, CollectionSchema, DataType, Collection, utility
def create_milvus_collection(collection_name, dim):
connections.connect(host='[10.97.4.101](http://10.97.4.101/)', port='19530')
if utility.has_collection(collection_name):
utility.drop_collection(collection_name)
fields = [
FieldSchema(name='id', dtype=DataType.INT64, descrition='ids', is_primary=True, auto_id=False),
FieldSchema(name='embedding', dtype=DataType.FLOAT_VECTOR, descrition='embedding vectors', dim=dim)
]
schema = CollectionSchema(fields=fields, description='reverse image search')
collection = Collection(name=collection_name, schema=schema)
# create IVF_FLAT index for collection.
index_params = {
'metric_type':'L2',
'index_type':"IVF_FLAT",
'params':{"nlist":2048}
}
collection.create_index(field_name="embedding", index_params=index_params)
return collection
通过中文文本搜索图片这个想法已经在我的想法清单中列了好久。
很苦恼的地方在于，自己手动训练模型的话，需要投入很多时间，做了很多调研，最终没有花时间去做。
很开心，看到towhee提供以文搜图的应用示例。
比较遗憾的是，目前只支持英文，期待能支持中文搜索图片
Hello~
I am trying the example video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb, but an error occurred that:
My towhee version is 1.0.0. Dose any one konw how to solve the problem?
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb 单元格 11 in 8
[3](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=2) from towhee.datacollection import DataCollection
[5](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=4) collection = create_milvus_collection('timesformer', 768)
[7](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=6) insert_pipe = (
----> [8](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=7) pipe.input('csv_path')
[9](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=8) .flat_map('csv_path', ('id', 'path', 'label'), read_csv)
[10](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=9) .map('id', 'id', lambda x: int(x))
[11](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=10) .map('path', 'frames', ops.video_decode.ffmpeg(sample_type='uniform_temporal_subsample', args={'num_samples': 8}))
[12](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=11) .map('frames', ('labels', 'scores', 'features'), ops.action_classification.timesformer(skip_preprocess=True))
[13](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=12) .map('features', 'features', ops.towhee.np_normalize())
[14](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=13) .map(('id', 'features'), 'insert_res', ops.ann_insert.milvus_client(host='127.0.0.1', port='19530', collection_name='timesformer'))
[15](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=14) .output()
[16](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=15) )
[18](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=17) insert_pipe('reverse_video_search.csv')
[20](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a2253485445435f646576656c6f70227d/home/image_check/code/examples/video/reverse_video_search/2_deep_dive_reverse_video_search.ipynb#X13sdnNjb2RlLXJlbW90ZQ%3D%3D?line=19) collection.load()
File [~/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/pipeline.py:116](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a2253485445435f646576656c6f70227d.vscode-resource.vscode-cdn.net/home/image_check/code/examples/video/reverse_video_search/~/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/pipeline.py:116), in Pipeline.output(self, *output_schema, **config_kws)
113 dag_dict[self._clo_node]['next_nodes'].append(uid)
115 run_pipe = RuntimePipeline(dag_dict, config=config_kws)
--> 116 run_pipe.preload()
117 return run_pipe
File [~/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/runtime_pipeline.py:140](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a2253485445435f646576656c6f70227d.vscode-resource.vscode-cdn.net/home/image_check/code/examples/video/reverse_video_search/~/anaconda3/envs/towhee/lib/python3.8/site-packages/towhee/runtime/runtime_pipeline.py:140), in RuntimePipeline.preload(self)
...
from .timesformer import Timesformer
File "/home/image_check/.towhee/operators/action-classification/timesformer/versions/main/timesformer.py", line 13, in
from towhee.models.utils.video_transforms import transform_video
ModuleNotFoundError: No module named 'towhee.models.utils.video_transforms'
Hello,l have try the example "image/reverse_image_search/2_deep_dive_image_search.ipynb", but an error occurred as follow. My towhee version is 1.1.0, Dose any body know how to solve this problem?
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[4], line 14
10 collection = create_milvus_collection(model, model_dim[model])
12 with Timer(f'{model} load'):
13 (
---> 14 towhee.read_csv('reverse_image_search.csv')
15 .runas_op['id', 'id'](func=lambda x: int(x))
16 .image_decode['path', 'img']()
17 .image_embedding.timm['img', 'vec'](model_name=model)
18 .tensor_normalize['vec', 'vec']()
19 .to_milvus['id', 'vec'](collection=collection, batch=100)
20 )
21 with Timer(f'{model} query'):
22 ( towhee.glob['path']('[./test/](https://vscode-remote+ssh-002dremote-002bheji-005frtx6000.vscode-resource.vscode-cdn.net/home/heji_rtx6000/code/examples_towhee2/image/reverse_image_search/test/)*/*.JPEG')
23 .image_decode['path', 'img']()
24 .image_embedding.timm['img', 'vec'](model_name=model)
(...)
31 .report()
32 )
AttributeError: module 'towhee' has no attribute 'read_csv'
Hi there :-）
Using milvus 2.0.2, and pymilvus is 2.0.2. Also using towhee 0.9.0 , pandas 2.0.1 and numpy 1.24.3
I got a new problem when I was running the program "Text Image Search" from examples. While running the step "Release a Showcase", an error occurred like:
Traceback (most recent call last):
File "/home/liu/anaconda3/envs/py39/lib/python3.9/site-packages/gradio/routes.py", line 401, in run_predict
output = await app.get_blocks().process_api(
File "/home/liu/anaconda3/envs/py39/lib/python3.9/site-packages/gradio/blocks.py", line 1302, in process_api
result = await self.call_function(
File "/home/liu/anaconda3/envs/py39/lib/python3.9/site-packages/gradio/blocks.py", line 1025, in call_function
prediction = await anyio.to_thread.run_sync(
File "/home/liu/anaconda3/envs/py39/lib/python3.9/site-packages/anyio/to_thread.py", line 31, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "/home/liu/anaconda3/envs/py39/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 937, in run_sync_in_worker_thread
return await future
File "/home/liu/anaconda3/envs/py39/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 867, in run
result = context.run(func, *args)
File "/tmp/ipykernel_606/2799569186.py", line 14, in search
image_ids = search_pipeline(text).to_list()[0][0]
AttributeError: 'DataQueue' object has no attribute 'to_list'
And the code "Release a Showcase" is below:
search_pipeline = (
pipe.input('text')
.map('text', 'vec', ops.image_text_embedding.clip(model_name='clip_vit_base_patch16', modality='text'))
.map('vec', 'vec', lambda x: x / np.linalg.norm(x))
.map('vec', 'result', ops.ann_search.milvus_client(host='127.0.0.1', port='19530', collection_name='text_image_search', limit=5))
.map('result', 'image_ids', lambda x: [item[0] for item in x])
.output('image_ids')
)
def search(text):
df = pd.read_csv('reverse_image_search.csv')
id_img = df.set_index('id')['path'].to_dict()
imgs = []
image_ids = search_pipeline(text).to_list()[0][0]
return [id_img[image_id] for image_id in image_ids]
import gradio
interface = gradio.Interface(search,
gradio.inputs.Textbox(lines=1),
[gradio.outputs.Image(type="filepath", label=None) for _ in range(5)]
)
interface.launch(inline=True, share=True)P.s. I once deleted the folder "~/.towhee/operator/ann-insert/milvus-client/" before because of #192 , and I don't know if this has any impact on this issue？
import cv2
from towhee.types.image import Image
def read_images(img_paths):
imgs = []
for p in img_paths:
imgs.append(Image(cv2.imread(p), 'BGR'))
return imgs
p_search_img = (
p_search_pre.map('pred', 'pred images', read_images)
.output('img', 'pred images')
)
DataCollection(p_search_img('test/goldfish/*.JPEG')).show()
needs to be updated from pred images to pred_images
TypeError Traceback (most recent call last)
Cell In[5], line 15
11 yield item
13 # Embedding pipeline
14 p_embed = (
---> 15 pipe.input('src')
16 .flat_map('src', 'img_path', load_image)
17 .map('img_path', 'img', ops.image_decode())
18 .map('img', 'vec', ops.image_embedding.timm(model_name=MODEL, device=DEVICE))
19 )
File ~/Desktop/Projects/vector_database/milvus/venv/lib/python3.8/site-packages/towhee/runtime/pipeline.py:143, in Pipeline.map(self, input_schema, output_schema, fn, config)
141 uid = uuid.uuid4().hex
142 fn_action = self._to_action(fn)
--> 143 dag_dict = deepcopy(self._dag)
144 dag_dict[uid] = {
145 'inputs': input_schema,
146 'outputs': output_schema,
(...)
153 'next_nodes': [],
154 }
155 dag_dict[self._clo_node]['next_nodes'].append(uid)
File /usr/lib/python3.8/copy.py:146, in deepcopy(x, memo, _nil)
144 copier = _deepcopy_dispatch.get(cls)
145 if copier is not None:
--> 146 y = copier(x, memo)
147 else:
148 if issubclass(cls, type):
File /usr/lib/python3.8/copy.py:230, in _deepcopy_dict(x, memo, deepcopy)
228 memo[id(x)] = y
229 for key, value in x.items():
--> 230 y[deepcopy(key, memo)] = deepcopy(value, memo)
231 return y
File /usr/lib/python3.8/copy.py:146, in deepcopy(x, memo, _nil)
144 copier = _deepcopy_dispatch.get(cls)
145 if copier is not None:
--> 146 y = copier(x, memo)
147 else:
148 if issubclass(cls, type):
File /usr/lib/python3.8/copy.py:230, in _deepcopy_dict(x, memo, deepcopy)
228 memo[id(x)] = y
229 for key, value in x.items():
--> 230 y[deepcopy(key, memo)] = deepcopy(value, memo)
231 return y
File /usr/lib/python3.8/copy.py:146, in deepcopy(x, memo, _nil)
144 copier = _deepcopy_dispatch.get(cls)
145 if copier is not None:
--> 146 y = copier(x, memo)
147 else:
148 if issubclass(cls, type):
File /usr/lib/python3.8/copy.py:230, in _deepcopy_dict(x, memo, deepcopy)
228 memo[id(x)] = y
229 for key, value in x.items():
--> 230 y[deepcopy(key, memo)] = deepcopy(value, memo)
231 return y
File /usr/lib/python3.8/copy.py:172, in deepcopy(x, memo, _nil)
170 y = x
171 else:
--> 172 y = _reconstruct(x, memo, *rv)
174 # If is its own copy, don't memoize.
175 if y is not x:
File /usr/lib/python3.8/copy.py:270, in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy)
268 if state is not None:
269 if deep:
--> 270 state = deepcopy(state, memo)
271 if hasattr(y, 'setstate'):
272 y.setstate(state)
File /usr/lib/python3.8/copy.py:146, in deepcopy(x, memo, _nil)
144 copier = _deepcopy_dispatch.get(cls)
145 if copier is not None:
--> 146 y = copier(x, memo)
147 else:
148 if issubclass(cls, type):
File /usr/lib/python3.8/copy.py:230, in _deepcopy_dict(x, memo, deepcopy)
228 memo[id(x)] = y
229 for key, value in x.items():
--> 230 y[deepcopy(key, memo)] = deepcopy(value, memo)
231 return y
File /usr/lib/python3.8/copy.py:161, in deepcopy(x, memo, _nil)
159 reductor = getattr(x, "reduce_ex", None)
160 if reductor is not None:
--> 161 rv = reductor(4)
162 else:
163 reductor = getattr(x, "reduce", None)
TypeError: cannot pickle '_thread.lock' object
Hello,
Im trying to follow the tuto here https://github.com/towhee-io/examples/blob/main/image/reverse_image_search/1_build_image_search_engine.ipynb
But when i test with 1K images and insert to milvus, the collection.num_entities gives me only 68 inserted. do you know what's wrong?
the code :
collection = create_milvus_collection('reverse_image_search', 128)
dc = (
towhee.glob'path'[:1000]
.image_decode'path', 'img'
.image_embedding.timm'img', 'vec'
.ann_insert.milvus('path', 'vec'), 'mr'
)
Node-image-text-embedding/clip-2 runs failed, error msg: Create image-text-embedding/clip-2 operator image-text-embedding/clip:main with args None and kws {'model_name': 'clip_vit_base_patch16', 'modality': 'image', 'device': 0} failed, err: Torch not compiled with CUDA enabled, Traceback (most recent call last): File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/towhee-0.9.1.dev111-py3.9.egg/towhee/runtime/nodes/node.py", line 88
in initialize, system: macOS Big Sur ，cuda: Intel Iris 1536 MB
I use jupyter notebook to import towhee 1.1.0,but failed
why? How can I solve this?
Hi, I'm new to towhee and want to have a try on the https://github.com/towhee-io/examples/blob/main/video/text_video_retrieval/1_text_video_retrieval_engine.ipynb, but the following block is running for hours:
collection = create_milvus_collection('text_video_retrieval', 512)
Found error log in docker logs milvus-standalone | grep ERROR
[2023/04/13 08:38:11.691 +00:00] [ERROR] [root_coord.go:1406] ["DescribeCollection failed"] [role=rootcoord] ["collection name"=text_video_retrieval] [msgID=440665421381737694] [error="can't find collection: text_video_retrieval"] [stack="github.com/milvus-io/milvus/internal/rootcoord.(*Core).DescribeCollection\n\t/go/src/github.com/milvus-io/milvus/internal/rootcoord/root_coord.go:1406\ngithub.com/milvus-io/milvus/internal/distributed/rootcoord.(*Server).DescribeCollection\n\t/go/src/github.com/milvus-io/milvus/internal/distributed/rootcoord/service.go:354\ngithub.com/milvus-io/milvus/internal/proto/rootcoordpb._RootCoord_DescribeCollection_Handler.func1\n\t/go/src/github.com/milvus-io/milvus/internal/proto/rootcoordpb/root_coord.pb.go:915\ngithub.com/grpc-ecosystem/go-grpc-middleware/tracing/opentracing.UnaryServerInterceptor.func1\n\t/go/pkg/mod/github.com/grpc-ecosystem/[email protected]/tracing/opentracing/server_interceptors.go:38\ngithub.com/milvus-io/milvus/internal/proto/rootcoordpb._RootCoord_DescribeCollection_Handler\n\t/go/src/github.com/milvus-io/milvus/internal/proto/rootcoordpb/root_coord.pb.go:917\ngoogle.golang.org/grpc.(*Server).processUnaryRPC\n\t/go/pkg/mod/google.golang.org/[email protected]/server.go:1286\ngoogle.golang.org/grpc.(*Server).handleStream\n\t/go/pkg/mod/google.golang.org/[email protected]/server.go:1609\ngoogle.golang.org/grpc.(*Server).serveStreams.func1.2\n\t/go/pkg/mod/google.golang.org/[email protected]/server.go:934"]
docker ps:
docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
a6490a7c84fe milvusdb/milvus:v2.0.2 "/tini -- milvus run…" 4 days ago Up 4 days 0.0.0.0:19530->19530/tcp milvus-standalone
781dfb9c3f61 quay.io/coreos/etcd:v3.5.0 "etcd -advertise-cli…" 4 days ago Up 4 days 2379-2380/tcp milvus-etcd
182fe7d79592 minio/minio:RELEASE.2020-12-03T00-03-10Z "/usr/bin/docker-ent…" 4 days ago Up 4 days (healthy) 9000/tcp milvus-minio
conda list:
# Name Version Build Channel
_libgcc_mutex 0.1 main
_openmp_mutex 5.1 1_gnu
aiofiles 23.1.0 pypi_0 pypi
aiohttp 3.8.4 pypi_0 pypi
aiosignal 1.3.1 pypi_0 pypi
altair 4.2.2 pypi_0 pypi
anyio 3.6.2 pypi_0 pypi
asttokens 2.2.1 pyhd8ed1ab_0 conda-forge
async-timeout 4.0.2 pypi_0 pypi
attrs 22.2.0 pypi_0 pypi
av 10.0.0 pypi_0 pypi
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
backports 1.0 pyhd8ed1ab_3 conda-forge
backports.functools_lru_cache 1.6.4 pyhd8ed1ab_0 conda-forge
bleach 6.0.0 pypi_0 pypi
bzip2 1.0.8 h7b6447c_0
ca-certificates 2022.12.7 ha878542_0 conda-forge
certifi 2022.12.7 pyhd8ed1ab_0 conda-forge
cffi 1.15.1 pypi_0 pypi
charset-normalizer 3.1.0 pypi_0 pypi
click 8.1.3 pypi_0 pypi
contourpy 1.0.7 pypi_0 pypi
cryptography 40.0.1 pypi_0 pypi
cycler 0.11.0 pypi_0 pypi
debugpy 1.5.1 py310h295c915_0
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
docutils 0.19 pypi_0 pypi
entrypoints 0.4 pyhd8ed1ab_0 conda-forge
executing 1.2.0 pyhd8ed1ab_0 conda-forge
fastapi 0.95.0 pypi_0 pypi
ffmpy 0.3.0 pypi_0 pypi
filelock 3.11.0 pypi_0 pypi
fonttools 4.39.3 pypi_0 pypi
frozenlist 1.3.3 pypi_0 pypi
fsspec 2023.4.0 pypi_0 pypi
gradio 3.24.1 pypi_0 pypi
gradio-client 0.0.8 pypi_0 pypi
grpcio 1.47.5 pypi_0 pypi
grpcio-tools 1.47.5 pypi_0 pypi
h11 0.14.0 pypi_0 pypi
httpcore 0.16.3 pypi_0 pypi
httpx 0.23.3 pypi_0 pypi
huggingface-hub 0.13.4 pypi_0 pypi
idna 3.4 pypi_0 pypi
importlib-metadata 6.2.0 pypi_0 pypi
ipykernel 6.15.0 pyh210e3f2_0 conda-forge
ipython 8.12.0 pyh41d4057_0 conda-forge
jaraco-classes 3.2.3 pypi_0 pypi
jedi 0.18.2 pyhd8ed1ab_0 conda-forge
jeepney 0.8.0 pypi_0 pypi
jinja2 3.1.2 pypi_0 pypi
jsonschema 4.17.3 pypi_0 pypi
jupyter_client 7.3.4 pyhd8ed1ab_0 conda-forge
jupyter_core 5.3.0 py310hff52083_0 conda-forge
keyring 23.13.1 pypi_0 pypi
kiwisolver 1.4.4 pypi_0 pypi
ld_impl_linux-64 2.38 h1181459_1
libffi 3.3 he6710b0_2
libgcc-ng 11.2.0 h1234567_1
libgomp 11.2.0 h1234567_1
libsodium 1.0.18 h36c2ea0_1 conda-forge
libstdcxx-ng 11.2.0 h1234567_1
libuuid 1.41.5 h5eee18b_0
linkify-it-py 2.0.0 pypi_0 pypi
markdown-it-py 2.2.0 pypi_0 pypi
markupsafe 2.1.2 pypi_0 pypi
matplotlib 3.7.1 pypi_0 pypi
matplotlib-inline 0.1.6 pyhd8ed1ab_0 conda-forge
mdit-py-plugins 0.3.3 pypi_0 pypi
mdurl 0.1.2 pypi_0 pypi
mmh3 3.0.0 pypi_0 pypi
more-itertools 9.1.0 pypi_0 pypi
multidict 6.0.4 pypi_0 pypi
ncurses 6.4 h6a678d5_0
nest-asyncio 1.5.6 pyhd8ed1ab_0 conda-forge
numpy 1.24.2 pypi_0 pypi
openssl 1.1.1t h7f8727e_0
orjson 3.8.9 pypi_0 pypi
packaging 23.0 pyhd8ed1ab_0 conda-forge
pandas 2.0.0 pypi_0 pypi
parso 0.8.3 pyhd8ed1ab_0 conda-forge
pexpect 4.8.0 pyh1a96a4e_2 conda-forge
pgzip 0.3.4 pypi_0 pypi
pickleshare 0.7.5 py_1003 conda-forge
pillow 9.5.0 pypi_0 pypi
pip 23.0.1 py310h06a4308_0
pkginfo 1.9.6 pypi_0 pypi
platformdirs 3.2.0 pyhd8ed1ab_0 conda-forge
prompt-toolkit 3.0.38 pyha770c72_0 conda-forge
prompt_toolkit 3.0.38 hd8ed1ab_0 conda-forge
protobuf 3.20.3 pypi_0 pypi
psutil 5.9.0 py310h5eee18b_0
ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge
pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
pyarrow 11.0.0 pypi_0 pypi
pycparser 2.21 pypi_0 pypi
pydantic 1.10.7 pypi_0 pypi
pydub 0.25.1 pypi_0 pypi
pygit2 1.10.1 pypi_0 pypi
pygments 2.14.0 pyhd8ed1ab_0 conda-forge
pymilvus 2.2.4 pypi_0 pypi
pyparsing 3.0.9 pypi_0 pypi
pyrsistent 0.19.3 pypi_0 pypi
python 3.10.0 h12debd9_5
python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge
python-multipart 0.0.6 pypi_0 pypi
python_abi 3.10 2_cp310 conda-forge
pytz 2023.3 pypi_0 pypi
pyyaml 6.0 pypi_0 pypi
pyzmq 23.2.0 py310h6a678d5_0
readline 8.2 h5eee18b_0
readme-renderer 37.3 pypi_0 pypi
requests 2.28.2 pypi_0 pypi
requests-toolbelt 0.10.1 pypi_0 pypi
rfc3986 1.5.0 pypi_0 pypi
rich 13.3.3 pypi_0 pypi
secretstorage 3.3.3 pypi_0 pypi
semantic-version 2.10.0 pypi_0 pypi
setuptools 65.6.3 py310h06a4308_0
six 1.16.0 pyh6c4a22f_0 conda-forge
sniffio 1.3.0 pypi_0 pypi
sqlite 3.41.1 h5eee18b_0
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
starlette 0.26.1 pypi_0 pypi
tabulate 0.9.0 pypi_0 pypi
tk 8.6.12 h1ccaba5_0
toolz 0.12.0 pypi_0 pypi
tornado 6.1 py310h5764c6d_3 conda-forge
towhee 0.9.0 pypi_0 pypi
towhee-models 0.9.0 pypi_0 pypi
tqdm 4.65.0 pypi_0 pypi
traitlets 5.9.0 pyhd8ed1ab_0 conda-forge
twine 4.0.2 pypi_0 pypi
typing-extensions 4.5.0 hd8ed1ab_0 conda-forge
typing_extensions 4.5.0 pyha770c72_0 conda-forge
tzdata 2023.3 pypi_0 pypi
uc-micro-py 1.0.1 pypi_0 pypi
ujson 5.4.0 pypi_0 pypi
urllib3 1.26.15 pypi_0 pypi
uvicorn 0.21.1 pypi_0 pypi
wcwidth 0.2.6 pyhd8ed1ab_0 conda-forge
webencodings 0.5.1 pypi_0 pypi
websockets 11.0.1 pypi_0 pypi
wheel 0.38.4 py310h06a4308_0
xz 5.2.10 h5eee18b_1
yarl 1.8.2 pypi_0 pypi
zeromq 4.3.4 h9c3ff4c_1 conda-forge
zipp 3.15.0 pypi_0 pypi
zlib 1.2.13 h5eee18b_0
我在运行search_article_in_medium.ipynb文件
执行下面代码的时候
from towhee import ops, pipe, DataCollection
insert_pipe = (pipe.input('df')
.flat_map('df', 'data', lambda df: df.values.tolist())
.map('data', 'res', ops.ann_insert.milvus_client(host='127.0.0.1',
port='19530',
collection_name='search_article_in_medium'))
.output('res')
)
错误信息：
Traceback (most recent call last):
File "D:\IT\python\Python38\lib\site-packages\IPython\core\interactiveshell.py", line 3398, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 3, in <cell line: 3>
insert_pipe = (pipe.input('df')
File "D:\IT\python\Python38\lib\site-packages\towhee\runtime\pipeline.py", line 103, in output
dag_dict = deepcopy(self._dag)
File "D:\IT\python\Python38\lib\copy.py", line 146, in deepcopy
y = copier(x, memo)
File "D:\IT\python\Python38\lib\copy.py", line 230, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "D:\IT\python\Python38\lib\copy.py", line 146, in deepcopy
y = copier(x, memo)
File "D:\IT\python\Python38\lib\copy.py", line 230, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "D:\IT\python\Python38\lib\copy.py", line 146, in deepcopy
y = copier(x, memo)
File "D:\IT\python\Python38\lib\copy.py", line 230, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "D:\IT\python\Python38\lib\copy.py", line 172, in deepcopy
y = _reconstruct(x, memo, *rv)
File "D:\IT\python\Python38\lib\copy.py", line 270, in _reconstruct
state = deepcopy(state, memo)
File "D:\IT\python\Python38\lib\copy.py", line 146, in deepcopy
y = copier(x, memo)
File "D:\IT\python\Python38\lib\copy.py", line 230, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "D:\IT\python\Python38\lib\copy.py", line 161, in deepcopy
rv = reductor(4)
TypeError: cannot pickle '_thread.lock' object
请问下是什么原因，怎么解决
我的towhee版本是 0.9.0
It should also be clear that the following dependencies need to be installed
2023-08-03 14:01:57,823 - 139852063110912 - image_decode_cv2.py-image_decode_cv2:40 - ERROR: Download image from http://904d20239a385ec9.jpg failed, error msg: {"Code":"NoSuchURL","Msg":"The specified URL does not exist."}, request code: 404
2023-08-03 14:01:57,823 - 139852063110912 - image_decode_cv2.py-image_decode_cv2:68 - ERROR: Read image http:///904d20239a385ec9.jpg failed
when i use pipe to get image feature,if the url link failure，The pipe program will jam without export nothing
import towhee
(
towhee.glob['path']('./train/tap_dancing/*.mp4').unstream()
.video_decode.ffmpeg['path', 'frames'](sample_type='uniform_temporal_subsample', args={'num_samples': 16})
.action_classification['frames', ('predicts', 'scores', 'features')].pytorchvideo(
model_name='x3d_m', skip_preprocess=True, topk=5)
.select['path', 'predicts', 'scores']()
.show()
)
towhee version
towhee-0.7.0-py3-none-any.whl
towhee.models-0.7.0-py3-none-any.whl
The above error was reported even though the relevant cache had been cleared locally
rm -rf ~/.cache/torch/hub/checkpoints/
rm -rf ~/.towhee/
Hi , I have a 24-hour audio , using NNFP for processing , reporting the error of not having enough memory . How can I fix the problem ? Here is the code.
emb_pipe = (
pipe.input('url')
.map('url', 'frames', ops.audio_decode.ffmpeg())
.map('frames', 'emb', ops.audio_embedding.nnfp())
)
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