Update app.py

app.py

@@ -4,11 +4,9 @@ import numpy as np
 
 def preprocess(img):
     img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-    img_blur = cv2.GaussianBlur(img_gray, (5, 5), 1)
-    img_canny = cv2.Canny(img_blur, 50, 50)
-    kernel = np.ones((3, 3))
-    img_dilate = cv2.dilate(img_canny, kernel, iterations=2)
-    img_erode = cv2.erode(img_dilate, kernel, iterations=1)
+    _, img_thresh = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY)
+    img_dilate = cv2.dilate(img_thresh, np.ones((3, 3)), iterations=2)
+    img_erode = cv2.erode(img_dilate, np.ones((3, 3)), iterations=1)
     return img_erode
 
 def find_tip(points, convex_hull):
@@ -25,16 +23,15 @@ def find_tip(points, convex_hull):
 def infer(image_in):
     img = cv2.imread(image_in)
 
-    contours, hierarchy = cv2.findContours(preprocess(img), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+    contours, _ = cv2.findContours(preprocess(img), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
 
     for cnt in contours:
-        peri = cv2.arcLength(cnt, True)
-        approx = cv2.approxPolyDP(cnt, 0.025 * peri, True)
+        approx = cv2.approxPolyDP(cnt, 0.02 * cv2.arcLength(cnt, True), True)
         hull = cv2.convexHull(approx, returnPoints=False)
         sides = len(hull)
 
         if 6 > sides > 3 and sides + 2 == len(approx):
-            arrow_tip = find_tip(approx[:,0,:], hull.squeeze())
+            arrow_tip = find_tip(approx[:, 0, :], hull.squeeze())
             if arrow_tip:
                 cv2.drawContours(img, [cnt], -1, (0, 255, 0), 3)
                 cv2.circle(img, arrow_tip, 3, (0, 0, 255), cv2.FILLED)
@@ -44,10 +41,10 @@ def infer(image_in):
     return "Image_result.png"
 
 gr.Interface(
-    fn = infer,
-    inputs = gr.Image(
-        sources = ["upload"],
-        type = "filepath"
+    fn=infer,
+    inputs=gr.Image(
+        sources=["upload"],
+        type="filepath"
     ),
-    outputs = gr.Image()
-).launch()
+    outputs=gr.Image()
+).launch()