Fix np, uda dev issue (#1272)

Limit numpy version to avoid issue with tensorboard, conv np.int to just int, fix  mismatched device issuecuda dev issue

requirements.txt

@@ -2,7 +2,7 @@
 
 # Base ----------------------------------------
 matplotlib>=3.2.2
-numpy>=1.18.5
+numpy>=1.18.5,<1.24.0
 opencv-python>=4.1.1
 Pillow>=7.1.2
 PyYAML>=5.3.1

utils/datasets.py

@@ -415,7 +415,7 @@ class LoadImagesAndLabels(Dataset):  # for training/testing
                 x[:, 0] = 0
 
         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(int)  # batch index
         nb = bi[-1] + 1  # number of batches
         self.batch = bi  # batch index of image
         self.n = n
@@ -443,7 +443,7 @@ class LoadImagesAndLabels(Dataset):  # for training/testing
                 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(int) * stride
 
         # Cache images into memory for faster training (WARNING: large datasets may exceed system RAM)
         self.imgs = [None] * n

utils/loss.py

@@ -739,7 +739,7 @@ class ComputeLossOTA:
                 + 3.0 * pair_wise_iou_loss
             )
 
-            matching_matrix = torch.zeros_like(cost)
+            matching_matrix = torch.zeros_like(cost, device="cpu")
 
             for gt_idx in range(num_gt):
                 _, pos_idx = torch.topk(