Comments (4)
you have to change the localization layers to output the center pixels.
or you can generate circles instead of rectangles using x1,y1,x2,y2 information to save effort
from frcnn-from-scratch-with-keras.
What is the current version of tensorflow-gpu does this support? Doesn't seem to work with tensorflow-gpu-1.12.1
from frcnn-from-scratch-with-keras.
can you try with 1.12.0? that is the version I used.
would be helpful if you can post error comments.
from frcnn-from-scratch-with-keras.
could you please tell about the tuning parameters ? I am already train the model with my custom data and I want to increase the model accuracy , so please tell me about model tuning parameters,
sir one more , this training goes very slowly and could you tell me about how can I increase the training speed ??
from frcnn-from-scratch-with-keras.
Related Issues (20)
- Why is the epoch_length is choosen as 1000? when should we change this? HOT 1
- Problem with AttributeError: 'str' object has no attribute 'shape' HOT 2
- Error during testing
- RPN is not producing bounding boxes that overlap the ground truth boxes. Check RPN settings or keep training.
- Anchor box generation when calculating the rpn HOT 1
- Unable to reproduce performance with PASCALVOC2010 and backbone resnet
- AttributeError: module 'tensorflow' has no attribute 'ConfigProto', how can I fix it ? HOT 1
- SystemExit: 2
- Can't train RPN separately (train_rpn.py)
- classifier_layers not used in resnet.py HOT 2
- RPN weights are not saved HOT 2
- How to write the results from the test_frcnn to a CSV file?
- Attempting to fetch value instead of handling error Internal: no supported devices found for platform CUDA
- Keyerror using measure_map for custom data using the trained VGG16 model
- Write the values of the predicted bounding boxes in measure_map
- How to plot feature maps from RPN model? HOT 1
- Cross Validation HOT 1
- Fit automated method instead of manually write it.
- Modify Network for Multi-task Learning
- ModuleNotFoundError: No module named 'tensorflow.compat.v1' HOT 1
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