I am working on an object detection project using Yolo-v3 algorithm using python.
Training model on 2 classes: Person and Football. I used a subset of images from the Coco dataset for the Person category and created the football dataset myself.
Training specs are as follows - Images Taken: 3500 * 2 classes = 7000 Batch Size: 64 Epochs: 60 each (unfreezed last layer and later unfreezing full network)
Tech Specs- Nvidia Tesla V100, Ubuntu, 32 gb RAM
Please help me with the following issues: 1. Unable to detect objects with intersecting bounding boxes i.e.,close object detection problem 2. Model is failing to detect both classes in a single picture
The loss functions seem to have stabilised -
Epoch 53/60 707/707 [==============================] - 463s 652ms/step - loss: 8.2134 - val_loss: 8.1215
Epoch 54/60 707/707 [==============================] - 454s 653ms/step - loss: 7.9846 - val_loss: 8.0124
Epoch 55/60 707/707 [==============================] - 461s 653ms/step - loss: 8.1012 - val_loss: 8.1344
Epoch 56/60 707/707 [==============================] - 455s 655ms/step - loss: 8.9814 - val_loss: 8.2155
Epoch 57/60 707/707 [==============================] - 460s 651ms/step - loss: 8.0459 - val_loss: 8.0664
Epoch 58/60 707/707 [==============================] - 465s 657ms/step - loss: 7.9934 - val_loss: 8.1552
Epoch 59/60 707/707 [==============================] - 459s 650ms/step - loss: 7.9364 - val_loss: 8.2638
Epoch 60/60 707/707 [==============================] - 461s 652ms/step - loss: 7.9426 - val_loss: 8.0902
Thanks in Advance, Michael