updates

utils/utils.py

@@ -56,9 +56,15 @@ def model_info(model, report='summary'):
 
 def labels_to_class_weights(labels, nc=80):
     # Get class weights (inverse frequency) from training labels
+    ni = len(labels)  # number of images
     labels = np.concatenate(labels, 0)  # labels.shape = (866643, 5) for COCO
     classes = labels[:, 0].astype(np.int)  # labels = [class xywh]
     weights = np.bincount(classes, minlength=nc)  # occurences per class
+
+    # Prepend gridpoint count (for uCE trianing)
+    # gpi = ((320 / 32 * np.array([1, 2, 4])) ** 2 * 3).sum()  # gridpoints per image
+    # weights = np.hstack([gpi * ni, weights])  # prepend gridpoints to start
+
     weights[weights == 0] = 1  # replace empty bins with 1
     weights = 1 / weights  # number of targets per class
     weights /= weights.sum()  # normalize