FIX: for runtime errors pertaining to numpy casting and loss function.

utils/datasets.py

@@ -409,7 +409,7 @@ def img2label_paths(img_paths):
         self.label_files = img2label_paths(cache.keys())  # update
 
         n = len(shapes)  # number of images
-        bi = np.floor(np.arange(n) / batch_size).astype(np.int)  # batch index
+        bi = np.floor(np.arange(n) / batch_size).astype(np.int64)  # batch index
         nb = bi[-1] + 1  # number of batches
         self.batch = bi  # batch index of image
         self.n = n
@@ -436,7 +436,7 @@ def img2label_paths(img_paths):
                 elif mini > 1:
                     shapes[i] = [1, 1 / mini]
 
-            self.batch_shapes = np.ceil(np.array(shapes) * img_size / stride + pad).astype(np.int) * stride
+            self.batch_shapes = np.ceil(np.array(shapes) * img_size / stride + pad).astype(np.int64) * stride
 
         # Check labels
         create_datasubset, extract_bounding_boxes, labels_loaded = False, False, False

utils/general.py

@@ -106,7 +106,7 @@ def labels_to_class_weights(labels, nc=80):
         return torch.Tensor()
 
     labels = np.concatenate(labels, 0)  # labels.shape = (866643, 5) for COCO
-    classes = labels[:, 0].astype(np.int)  # labels = [class xywh]
+    classes = labels[:, 0].astype(np.int64)  # labels = [class xywh]
     weights = np.bincount(classes, minlength=nc)  # occurrences per class
 
     # Prepend gridpoint count (for uCE training)

utils/loss.py

@@ -174,7 +174,7 @@ def build_targets(p, targets, model):
 
         # Append
         a = t[:, 6].long()  # anchor indices
-        indices.append((b, a, gj.clamp_(0, gain[3] - 1), gi.clamp_(0, gain[2] - 1)))  # image, anchor, grid indices
+        indices.append((b, a, gj.clamp_(0, int(gain[3]) - 1), gi.clamp_(0, int(gain[2]) - 1)))  # image, anchor, grid indices
         tbox.append(torch.cat((gxy - gij, gwh), 1))  # box
         anch.append(anchors[a])  # anchors
         tcls.append(c)  # class