Create app.py

app.py

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+import cv2
+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)
+    return img_erode
+
+def find_tip(points, convex_hull):
+    length = len(points)
+    indices = np.setdiff1d(range(length), convex_hull)
+
+    for i in range(2):
+        j = indices[i] + 2
+        if j > length - 1:
+            j = length - j
+        if np.all(points[j] == points[indices[i - 1] - 2]):
+            return tuple(points[j])
+
+def infer(image_in):
+    img = cv2.imread(image_in)
+
+    contours, hierarchy = cv2.findContours(preprocess(img), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+
+    for cnt in contours:
+        peri = cv2.arcLength(cnt, True)
+        approx = cv2.approxPolyDP(cnt, 0.025 * peri, 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())
+            if arrow_tip:
+                cv2.drawContours(img, [cnt], -1, (0, 255, 0), 3)
+                cv2.circle(img, arrow_tip, 3, (0, 0, 255), cv2.FILLED)
+
+    cv2.imwrite("Image_result.png", img)
+
+    return "Image_result.png"
+
+gr.Interface(
+    fn = infer,
+    inputs = gr.Image(
+        sources = "upload",
+        type = "filepath"
+    ),
+    outputs = gr.Image()
+).launch()