Spaces:
Running
on
T4
Running
on
T4
Update app.py
Browse files
app.py
CHANGED
@@ -29,7 +29,7 @@ def get_point(point_type, tracking_points, trackings_input_label, first_frame_pa
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transparent_layer = np.zeros((h, w, 4))
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for index, track in enumerate(tracking_points.value):
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if trackings_input_label.value[index] == 1:
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cv2.circle(transparent_layer, track, 20, (0,
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else:
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cv2.circle(transparent_layer, track, 20, (255, 0, 0, 255), -1)
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@@ -98,23 +98,19 @@ def show_masks(image, masks, scores, point_coords=None, box_coords=None, input_l
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plt.close() # Close the figure to free up memory
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# ---- Separate Mask Image ----
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mask_image = np.zeros_like(image, dtype=np.uint8)
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plt.gca().xaxis.set_major_locator(plt.NullLocator())
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plt.gca().yaxis.set_major_locator(plt.NullLocator())
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# Save mask image
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mask_filename = f"mask_image_{i+1}.png"
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mask_images.append(mask_filename)
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plt.close() # Close the figure to free up memory
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transparent_layer = np.zeros((h, w, 4))
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for index, track in enumerate(tracking_points.value):
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if trackings_input_label.value[index] == 1:
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cv2.circle(transparent_layer, track, 20, (0, 255, 0, 255), -1)
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else:
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cv2.circle(transparent_layer, track, 20, (255, 0, 0, 255), -1)
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plt.close() # Close the figure to free up memory
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# ---- Separate Mask Image (White Mask on Black Background) ----
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# Create a black image
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mask_image = np.zeros_like(image, dtype=np.uint8)
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# The mask is a binary array where the masked area is 1, else 0.
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# Convert the mask to a white color in the mask_image
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mask_layer = (mask > 0).astype(np.uint8) * 255
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for c in range(3): # Assuming RGB, repeat mask for all channels
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mask_image[:, :, c] = mask_layer
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# Save the mask image
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mask_filename = f"mask_image_{i+1}.png"
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Image.fromarray(mask_image).save(mask_filename)
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mask_images.append(mask_filename)
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plt.close() # Close the figure to free up memory
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