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fix: RuntimeError: result type Float can't be cast to the desired output type long int #271

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fix: RuntimeError: result type Float can't be cast to the desired output type long int #271

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7 changes: 5 additions & 2 deletions utils/loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -133,9 +133,12 @@ def build_targets(p, targets, model):
g = 0.5 # offset
multi_gpu = is_parallel(model)
for i, jj in enumerate(model.module.yolo_layers if multi_gpu else model.yolo_layers):
# fixes torch==1.12 compatibility (implements ultralytics/yolov5 pr #8067)
shape = p[i].shape

# get number of grid points and anchor vec for this yolo layer
anchors = model.module.module_list[jj].anchor_vec if multi_gpu else model.module_list[jj].anchor_vec
gain[2:] = torch.tensor(p[i].shape)[[3, 2, 3, 2]] # xyxy gain
gain[2:] = torch.tensor(shape)[[3, 2, 3, 2]] # xyxy gain

# Match targets to anchors
a, t, offsets = [], targets * gain, 0
Expand Down Expand Up @@ -164,7 +167,7 @@ def build_targets(p, targets, model):

# Append
#indices.append((b, a, gj, gi)) # image, anchor, grid 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, shape[2] - 1), gi.clamp_(0, shape[3] - 1))) # image, anchor, grid indices
tbox.append(torch.cat((gxy - gij, gwh), 1)) # box
anch.append(anchors[a]) # anchors
tcls.append(c) # class
Expand Down