Create app.py

app.py

@@ -0,0 +1,70 @@
+import base64
+import cv2
+import numpy as np
+import os
+from fastapi import FastAPI
+from pydantic import BaseModel
+from collections import defaultdict
+
+app = FastAPI()
+
+class Input(BaseModel):
+    image_base64: str
+
+def save_base64_image_cv(base64_str, output_path="final.png"):
+    img_data = base64.b64decode(base64_str)
+    nparr = np.frombuffer(img_data, np.uint8)
+    img = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
+
+    if img.shape[2] == 4:
+        alpha = img[:, :, 3] / 255.0
+        rgb = img[:, :, :3]
+        white_bg = np.ones_like(rgb, dtype=np.uint8) * 255
+        img = (rgb * alpha[:, :, None] + white_bg * (1 - alpha[:, :, None])).astype(np.uint8)
+
+    cv2.imwrite(output_path, img)
+
+def extract_icon_positions(image_path):
+    img = cv2.imread(image_path)
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    _, thresh = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY_INV)
+    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    icons, pos = [], []
+    for c in contours:
+        x, y, w, h = cv2.boundingRect(c)
+        if w > 10 and h > 10:
+            roi = cv2.resize(thresh[y:y+h, x:x+w], (50, 50))
+            icons.append(roi)
+            pos.append((x, y))
+    return icons, pos
+
+def img_hash(img):
+    img = cv2.resize(img, (8, 8))
+    return (img > img.mean()).astype(np.uint8).flatten()
+
+def find_rarest(icon_features, positions):
+    hashes = [img_hash(i) for i in icon_features]
+    groups = defaultdict(list)
+
+    for i, h in enumerate(hashes):
+        for g in groups.values():
+            if np.sum(h != hashes[g[0]]) < 3:
+                g.append(i)
+                break
+        else:
+            groups[len(groups)] = [i]
+
+    idx = min(groups.values(), key=len)[0]
+    return positions[idx]
+
+@app.post("/solve")
+def solve(data: Input):
+    try:
+        save_base64_image_cv(data.image_base64)
+        icons, pos = extract_icon_positions("final.png")
+        x, y = find_rarest(icons, pos)
+        return {"x": x, "y": y}
+    finally:
+        if os.path.exists("final.png"):
+            os.remove("final.png")