updates

Dockerfile

@@ -0,0 +1,23 @@
+# Start from Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
+FROM nvcr.io/nvidia/pytorch:19.07-py3
+
+# Install dependencies
+RUN pip3 install -U -r requirements.txt
+
+# Move file into container
+# RUN mv 1047.tif ./1047.tif
+
+# Move model into container
+# RUN mv yolov3-spp.pt ./weights
+
+
+# ---------------------------------------------------  Extras Below  ---------------------------------------------------
+
+# Build container
+# sudo docker image prune -a && sudo docker build -t friendlyhello . && sudo docker tag friendlyhello ultralytics/yolov3:v0
+
+# Run container
+# time sudo docker run -it --memory=8g --cpus=4 ultralytics/yolov3:v0 bash -c './run.sh /1047.tif /tmp && cat /tmp/1047.tif.txt'
+
+# Push container to https://hub.docker.com/u/ultralytics
+# sudo docker push ultralytics/xview:v30

utils/utils.py

@@ -291,7 +291,7 @@ def wh_iou(box1, box2):
 class FocalLoss(nn.Module):
     # Wraps focal loss around existing loss_fcn() https://arxiv.org/pdf/1708.02002.pdf
     # i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=2.5)
-    def __init__(self, loss_fcn, alpha=1, gamma=2, reduction='mean'):
+    def __init__(self, loss_fcn, alpha=1, gamma=0.5, reduction='mean'):
         super(FocalLoss, self).__init__()
         loss_fcn.reduction = 'none'  # required to apply FL to each element
         self.loss_fcn = loss_fcn