However, on my test image, no bounding boxes are shown.
Can someone enlighten me on where the problem might be?
Also in the log for the aforementioned script, I encounter this warning:
Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature.
Is there someway to get rid of this warning?
P.S. I trained the network on Geforce RTX 2080 8GB.
I've attached the image. In expected case, there should be a bounding box around the 100 speed limit traffic sign.
All the inputs are highly appreciated. Thank you :)
I have successfully trained the retinanet with ResNet50 backbone consuming a whooping 5 hours. I ran the detection using the following script : https://github.com/fizyr/keras-retinanet/blob/master/examples/ResNet50RetinaNet.py
However, on my test image, no bounding boxes are shown.
Can someone enlighten me on where the problem might be?
Also in the log for the aforementioned script, I encounter this warning:
Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature.
Is there someway to get rid of this warning?
P.S. I trained the network on Geforce RTX 2080 8GB.
I've attached the image. In expected case, there should be a bounding box around the 100 speed limit traffic sign.
All the inputs are highly appreciated. Thank you :)