Update app.py
Browse files
app.py
CHANGED
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@@ -8,7 +8,7 @@ from itertools import chain
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from transformers import SamModel, SamProcessor
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model = SamModel.from_pretrained('facebook/sam-vit-huge')
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processor = SamProcessor.from_pretrained('facebook/sam-vit-huge')
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@@ -16,7 +16,7 @@ def set_predictor(image):
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"""
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Creates a Sam predictor object based on a given image and model.
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"""
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device = '
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inputs = processor(image, return_tensors='pt').to(device)
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image_embedding = model.get_image_embeddings(inputs['pixel_values'])
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@@ -28,11 +28,9 @@ def get_polygon(points, image, image_embedding):
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Returns the points of the polygon given a bounding box and a prediction
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made by Sam.
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"""
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#points = [int(w) for w in points.split(',')]
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points = list(chain.from_iterable(points))
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print(points)
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device = '
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inputs = processor(image, input_boxes=[points], return_tensors="pt").to(device)
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# pop the pixel_values as they are not neded
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from transformers import SamModel, SamProcessor
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model = SamModel.from_pretrained('facebook/sam-vit-huge')
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processor = SamProcessor.from_pretrained('facebook/sam-vit-huge')
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"""
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Creates a Sam predictor object based on a given image and model.
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"""
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device = 'cpu'
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inputs = processor(image, return_tensors='pt').to(device)
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image_embedding = model.get_image_embeddings(inputs['pixel_values'])
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Returns the points of the polygon given a bounding box and a prediction
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made by Sam.
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"""
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points = list(chain.from_iterable(points))
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device = 'cpu'
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inputs = processor(image, input_boxes=[points], return_tensors="pt").to(device)
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# pop the pixel_values as they are not neded
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