blend sample image and viz

yolov5.py

@@ -234,10 +234,15 @@ def dff_nmf(image, target_lyr, n_components):
         fig.canvas.draw()  # Draw the canvas to make sure the image is rendered
         image_array = np.array(fig.canvas.renderer.buffer_rgba())  # Convert to numpy array
         print("____________image_arrya", image_array.shape)
+        image_resized = cv2.resize(image_array, (640, 640))
+        rgba_channels = cv2.split(image_resized)
+        alpha_channel = rgba_channels[3] / 255.0
+        rgb_channels = np.stack(rgba_channels[:3], axis=-1)
+        overlay_img = (alpha_channel[..., None] * image) + ((1 - alpha_channel[..., None]) * rgb_channels)
         
         #temp = image_array.reshape((rgb_img_float.shape[0],rgb_img_float.shape[1]) )
-        visualization = show_factorization_on_image(rgb_img_float, image_array.resize((rgb_img_float.shape)) , image_weight=0.3)
-        results.append(visualization)
+        #visualization = show_factorization_on_image(rgb_img_float, image_array.resize((rgb_img_float.shape)) , image_weight=0.3)
+        results.append(overlay_img)
         plt.clf()  
         #return image_array