Comments (1)
BichenWuUCB
commented on July 22, 2024
One more thing you need to change is the last layer's channel size. Recall that in the ConvDet layer in squeezeDet, the output channel size is K(C+5) where K is the number of anchors, C is the number of classes, and 5 is 1 confidence score + 4 coordinates.
There might be something else that you need to change, but the best way to figure that out is to play with the code.
Good luck.
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Related Issues (20)
- Gpu occupancy rate
- where is base_model_config.py?
- Will random initialization parameters have no precision? HOT 1
- Fine-tune SqueezeDet from sparse labels
- How to do hard negative mining HOT 1
- Publish frozen model? HOT 3
- Problem converting to TFLite HOT 3
- low GPU usage
- 8-bit weights
- Deploying squeezeDet on mobile HOT 3
- How to convert checkpoint of squeezedet to frozen graph for tflite conversion?! HOT 1
- Image resolution problem
- How to run demo.py using train.py checkpoint model HOT 1
- Train with different size and Inference with different size.
- Fine tuning with the model
- Train error and Eval error
- Using negative samples for training.
- print weights per layer during training
- Performance issue in src/eval.py (by P3) HOT 1
- The loss plateaus after 100 Epoch
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