Update app.py

app.py

@@ -44,7 +44,7 @@ def get_masks(prompts, img, threhsold):
     return masks
 
 
-def extract_image(img, pos_prompts, neg_prompts, threshold, alpha_value=0.5):
+def extract_image(img, pos_prompts, neg_prompts, threshold, alpha_value):
     positive_masks = get_masks(pos_prompts, img, threshold)
     negative_masks = get_masks(neg_prompts, img, threshold)
 
@@ -61,15 +61,19 @@ def extract_image(img, pos_prompts, neg_prompts, threshold, alpha_value=0.5):
     mask_rgba = Image.new("RGBA", img.size, (0, 0, 0, 0))
     mask_rgba.paste(final_mask_img, (0, 0), final_mask_img)
 
-    # blend the original image and the mask using the alpha value
-    output_image = Image.blend(img_rgba, mask_rgba, alpha_value)
+    # apply alpha value to final_mask
+    alpha_mask = Image.fromarray((final_mask * 255 * alpha_value).astype(np.uint8), "L")
+    inverse_alpha_mask = Image.fromarray(((1 - final_mask) * 255 * alpha_value).astype(np.uint8), "L")
 
     # extract the final image
-    final_mask = Image.fromarray(final_mask.astype(np.uint8) * 255, "L")
-    inverse_mask = np.invert(final_mask)
+    output_image = Image.new("RGBA", img.size, (0, 0, 0, 0))
+    output_image.paste(img, mask=alpha_mask)
 
-    return output_image, final_mask, inverse_mask
+    # extract the inverse_mask
+    output_inverse_image = Image.new("RGBA", img.size, (0, 0, 0, 0))
+    output_inverse_image.paste(img, mask=inverse_alpha_mask)
 
+    return output_image, alpha_mask, inverse_alpha_mask
 
 
 title = "Interactive demo: zero-shot image segmentation with CLIPSeg"