Update app.py
Browse files
app.py
CHANGED
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@@ -3,7 +3,6 @@ from skimage.metrics import structural_similarity as ssim
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import gradio as gr
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import cv2
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# Function to calculate SSIM between two images
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def calculate_similarity(img1, img2):
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if len(img1.shape) == 2:
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img1 = cv2.cvtColor(img1, cv2.COLOR_GRAY2RGB)
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@@ -13,19 +12,9 @@ def calculate_similarity(img1, img2):
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max_width = max(img1.shape[1], img2.shape[1])
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img1_resized = cv2.resize(img1, (max_width, max_height))
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img2_resized = cv2.resize(img2, (max_width, max_height))
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ssim_score = ssim(img1_resized, img2_resized, win_size=3, multichannel=True)
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# Additional score calculation after text removal (modify this as per your requirement)
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text_removed_score = 0.75 # Placeholder value, replace with your own calculation
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# Combine the scores or choose the desired score
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combined_score = (ssim_score + text_removed_score) / 2
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return combined_score
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# Rest of the code remains the same
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def image_similarity(img1, img2):
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img1 = img1.astype(np.uint8)
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img2 = img2.astype(np.uint8)
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@@ -44,4 +33,4 @@ iface = gr.Interface(
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description="Upload two images to compute their similarity."
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)
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iface.launch()
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import gradio as gr
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import cv2
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def calculate_similarity(img1, img2):
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if len(img1.shape) == 2:
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img1 = cv2.cvtColor(img1, cv2.COLOR_GRAY2RGB)
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max_width = max(img1.shape[1], img2.shape[1])
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img1_resized = cv2.resize(img1, (max_width, max_height))
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img2_resized = cv2.resize(img2, (max_width, max_height))
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similarity_score = ssim(img1_resized, img2_resized, multichannel=True)
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return similarity_score
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def image_similarity(img1, img2):
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img1 = img1.astype(np.uint8)
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img2 = img2.astype(np.uint8)
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description="Upload two images to compute their similarity."
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)
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iface.launch(share=True)
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