Update app.py
Browse files
app.py
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@@ -14,10 +14,14 @@ train_tfms = tfms.A.Adapter(
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valid_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size), tfms.A.Normalize()])
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# model1 = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True), num_classes=len(class_map))
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model1 = faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True), num_classes=len(class_map))
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state_dict = torch.load('fasterRCNNFruits.pth', map_location=torch.device('cpu'))
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model1.load_state_dict(state_dict)
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def show_preds(input_image, display_label, display_bbox, detection_threshold):
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)
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valid_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(size), tfms.A.Normalize()])
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backbone = faster_rcnn.backbones.resnet_fpn.resnet18(pretrained=True)
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model1 = faster_rcnn.model(backbone=backbone, num_classes=len(class_map))
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model1.load_state_dict(torch.load('fasterRCNNFruits.pth', map_location=torch.device('cpu')))
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# model1 = models.torchvision.faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True), num_classes=len(class_map))
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# model1 = faster_rcnn.model(backbone=models.torchvision.faster_rcnn.backbones.resnet18_fpn(pretrained=True), num_classes=len(class_map))
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# state_dict = torch.load('fasterRCNNFruits.pth', map_location=torch.device('cpu'))
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# model1.load_state_dict(state_dict)
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def show_preds(input_image, display_label, display_bbox, detection_threshold):
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