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Update app.py
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app.py
CHANGED
@@ -6,6 +6,11 @@ from timm import create_model
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from timm.data import resolve_data_config
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from timm.data.transforms_factory import create_transform
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IMAGENET_1K_URL = "https://storage.googleapis.com/bit_models/ilsvrc2012_wordnet_lemmas.txt"
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LABELS = requests.get(IMAGENET_1K_URL).text.strip().split("\n")
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model = create_model('resnet50', pretrained=True)
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@@ -25,5 +30,10 @@ def predict_fn(img):
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values, indices = torch.topk(probabilities, k=3)
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return {LABELS[i]: v.item() for i, v in zip(indices, values)}
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gr.Interface(predict_fn,
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from timm.data import resolve_data_config
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from timm.data.transforms_factory import create_transform
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title = "Image Classifier Four -- Timm Resnet-50"
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description = """This machine has vision. It can see objects and concepts in an image. To test the machine, upload or drop an image, submit and read the results. The results comprise a list of words that the machine sees in the image. Beside a word, the length of the bar indicates the confidence with which the machine sees the word. The longer the bar, the more confident the machine is.
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"""
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article = "This app was made by following [this YouTube video](https://youtu.be/a8aS3ZYlzDM)."
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IMAGENET_1K_URL = "https://storage.googleapis.com/bit_models/ilsvrc2012_wordnet_lemmas.txt"
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LABELS = requests.get(IMAGENET_1K_URL).text.strip().split("\n")
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model = create_model('resnet50', pretrained=True)
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values, indices = torch.topk(probabilities, k=3)
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return {LABELS[i]: v.item() for i, v in zip(indices, values)}
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gr.Interface(predict_fn,
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gr.inputs.Image(type='pil'),
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outputs='label',
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title = title,
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description = description,
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article = article).launch()
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