Comments (4)
Thanks @MotzWanted. Currently I have limited time to provide support for this library, but I want to rewrite the Python bindings for a faster inference very soon. I'll test and verify it on different platforms then.
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During the first implementation of Python bindings, signatures of functions for batch processing were not compatible with ctypes --they were accepting a std::vector
instead of a custom struct. I refactored it in the C/C++ code later on but didn't implement on the Python side. This will be fixed in the upcoming implementation.
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I've solved the issue. I verify symbol export in the compiled library by using the nm
tool on macOS:
nm -gU /path/to/libclip.dylib
I look for make_clip_image_u8
and make_clip_image_f32
in the output, and find similar functions named _clip_image_u8_make
and _clip_image_f32_make
. I change the naming in line 202 and line 206 which solves the AttributeError
.
from clip.cpp.
No worries @monatis. Let me know if I can be of any help to you... Btw. can you tell me why you have marked out clip_image_batch_encode?
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Related Issues (20)
- convert Chinese clip model
- Introduce Java bindings HOT 1
- Support batch inference for models other than patch32 HOT 3
- python bindings🐍: Support for accepting list of Input in the encoding methods HOT 7
- Implement bicubic interpolation HOT 4
- Can u please make exe of this project? HOT 2
- no module named 'gguf' HOT 2
- Metal support? HOT 5
- Building with -DCLIP_BUILD_IMAGE_SEARCH=ON for image-search fails, ‘cos_gt’ is not a member of ‘unum::usearch’ HOT 4
- Vision only model memory issue
- Slower image encode the lower the quantization HOT 1
- Memory leak: clip_tokenize and clip_image_preprocess HOT 2
- Question about the CLIP model in clip.cpp and llama.cpp HOT 1
- include clip.cpp in another project
- Python Bindings, optionally pass PIL image
- Python Bindings distributions for different architectures
- Windows Compilation HOT 1
- clip_image_preprocess() produces incorrect results for images with height > width
- (Possible) Incorrect assignment of image mean/std values in `clip_model_load()`
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