tmp

app.py

@@ -119,20 +119,18 @@ def generate_matching_superfeatures(im1, im2, scale_id=6, threshold=50):
     fig1 = plt.figure(1)
     plt.imshow(cv2.cvtColor(img1rsz, cv2.COLOR_BGR2RGB))
     ax1 = plt.gca()
-    ax1.axis('scaled')
+    # ax1.axis('scaled')
     ax1.axis('off')
-
     plt.tight_layout()    
-    fig1.canvas.draw()
+    # fig1.canvas.draw()
     
     fig2 = plt.figure(2)
     plt.imshow(cv2.cvtColor(img2rsz, cv2.COLOR_BGR2RGB))
     ax2 = plt.gca()
-    ax2.axis('scaled')
+    # ax2.axis('scaled')
     ax2.axis('off')
-    
     plt.tight_layout()    
-    fig2.canvas.draw()
+    # fig2.canvas.draw()
        
     # fig = plt.figure()
     # grid = ImageGrid(fig, 111, nrows_ncols=(2, 1),  axes_pad=0.1)
@@ -147,7 +145,7 @@ def generate_matching_superfeatures(im1, im2, scale_id=6, threshold=50):
     # # Now we can save it to a numpy array.
     # data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
     # data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
-    return fig1,fig2
+    return fig1, fig2
 
 
 # GRADIO APP