Update app.py

app.py

@@ -298,7 +298,7 @@ def get_mesh(image, depth, blur_data, loadall):
     clrs = [[128,128,128,0]]
 
     #for i in range(0,1): #(0,4)
-        clrs = np.concatenate((clrs, colors), axis=0)
+    clrs = np.concatenate((clrs, colors), axis=0)
         #i = i+1
 
     #triangles = create_triangles(rgba.shape[0], rgba.shape[1])
@@ -438,25 +438,26 @@ def optimize(v, d):
             # convert to np.float32
             f = np.float32(frame.reshape((-1,3)))
             # define criteria, number of clusters(K) and apply kmeans()
-            criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
-            ret,label,center=cv2.kmeans(f,l,None,criteria,10,cv2.KMEANS_RANDOM_CENTERS)
+            criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 4, 1.0)
+            ret,label,center=cv2.kmeans(f,l,None,criteria,4,cv2.KMEANS_RANDOM_CENTERS)
             # Now convert back into uint8, and make original image
             center = np.uint8(center)
             res = center[label.flatten()]
             frame = res.reshape((frame.shape))
 
-            dcolor.append(bincount(frame))
+            depth = cv2.imread(depths[k]).astype(np.uint8)
+            sky = depth[(depth==0).all()]
+            dcolor.append(bincount(frame[sky>0]))
             print(dcolor[k])
             
-            mask = cv2.convertScaleAbs(cv2.Laplacian(cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY), ddepth, ksize=kernel_size))
-            mask[mask>0] = 255
-            frame[mask==0] = (0, 0, 0)
+            #mask = cv2.convertScaleAbs(cv2.Laplacian(cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY), ddepth, ksize=kernel_size))
+            #mask[mask>0] = 255
+            #frame[mask==0] = (0, 0, 0)
             cv2.imwrite(frames[k], frame)
 
-            depth = cv2.imread(depths[k]).astype(np.uint8)
-            depth[mask==0] = (255,255,255)
-            #mask = cv2.inRange(frame, np.array([dcolor[k][0]-8, dcolor[k][1]-8, dcolor[k][2]-8]), np.array([dcolor[k][0]+8, dcolor[k][1]+8, dcolor[k][2]+8]))
-            #depth[mask>0] = (255,255,255)
+            #depth[mask==0] = (255,255,255)
+            mask = cv2.inRange(frame, np.array([dcolor[k][0]-8, dcolor[k][1]-8, dcolor[k][2]-8]), np.array([dcolor[k][0]+8, dcolor[k][1]+8, dcolor[k][2]+8]))
+            depth[mask>0] = (255,255,255)
             depth[depth.shape[0]-1:depth.shape[0], 0:depth.shape[1]] = (160, 160, 160)
             depth[0:1, 0:depth.shape[1]] = (0, 0, 0)
             cv2.imwrite(depths[k], depth)