I encountered this problem when running the following script
python demo.py --config-file .\configs\CoDet_OVCOCO_R50_1x.yaml --input ..\VLDet\heatmap_inputs\000000059598.jpg --output .\demo_outputs\ --vocabulary co
co --opts MODEL.WEIGHTS .\models\CoDet_OVCOCO_R50_1x..pth
Traceback (most recent call last):
File "demo.py", line 140, in <module>
demo = VisualizationDemo(cfg, args)
File "E:\VLDet\CoDet\codet\predictor.py", line 68, in __init__
reset_cls_infer(self.predictor.model, classifier, num_classes)
File "E:\VLDet\CoDet\codet\modeling\utils.py", line 63, in reset_cls_infer
if model.roi_heads.box_predictor[0].cls_score.norm_weight:
TypeError: 'CoDetFastRCNNOutputLayers' object is not subscriptable
Afterwards, I modified the code in the reset_cls_infer function and it can be run
def reset_cls_infer(model, cls_path, num_classes):
model.roi_heads.num_classes = num_classes
if type(cls_path) == str:
print('Resetting zs_weight', cls_path)
zs_weight = torch.tensor(
np.load(cls_path),
dtype=torch.float32).permute(1, 0).contiguous() # D x C
else:
zs_weight = cls_path
zs_weight = torch.cat(
[zs_weight, zs_weight.new_zeros((zs_weight.shape[0], 1))],
dim=1) # D x (C + 1)
if model.roi_heads.box_predictor.cls_score.norm_weight:
# if model.roi_heads.box_predictor[0].cls_score.norm_weight:
zs_weight = F.normalize(zs_weight, p=2, dim=0)
zs_weight = zs_weight.to(model.device)
# for k in range(len(model.roi_heads.box_predictor)):
# del model.roi_heads.box_predictor[k].cls_score.detection_weight
# model.roi_heads.box_predictor[k].cls_score.detection_weight = zs_weight
del model.roi_heads.box_predictor.cls_score.detection_weight
model.roi_heads.box_predictor.cls_score.detection_weight = zs_weight
I want to know if what I'm doing is correct
