Update app.py

app.py

@@ -1,96 +1,95 @@
 import base64, cv2, numpy as np
-‎from fastapi import FastAPI
-‎from pydantic import BaseModel
-‎import uvicorn
-‎
-‎app = FastAPI(
-‎    title="IconCaptcha Solver API",
-‎    version="1.0",
-‎    description="Solver IconCaptcha - return click point, bounding box, and edited image"
-‎)
-‎
-‎class SolveRequest(BaseModel):
-‎    widgetId: str
-‎    challengeId: str
-‎    image_base64: str
-‎
-‎
-‎def b64_to_image(b64):
-‎    nparr = np.frombuffer(base64.b64decode(b64), np.uint8)
-‎    img = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
-‎
-‎    if img.shape[2] == 4:   # transparan → ubah ke background putih
-‎        alpha = img[:,:,3] / 255.0
-‎        rgb   = img[:,:,:3]
-‎        bg    = np.ones_like(rgb)*255
-‎        img   = (rgb*alpha[:,:,None] + bg*(1-alpha[:,:,None])).astype(np.uint8)
-‎
-‎    return img
-‎
-‎
-‎def extract_icons(img):
-‎    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-‎    _,thr = cv2.threshold(gray,200,255,cv2.THRESH_BINARY_INV)
-‎    cnt,_ = cv2.findContours(thr,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
-‎
-‎    icons,pos=[],[]
-‎    for c in cnt:
-‎        x,y,w,h=cv2.boundingRect(c)
-‎        if w>20 and h>20:
-‎            roi=cv2.resize(thr[y:y+h,x:x+w],(50,50))
-‎            icons.append(roi)
-‎            pos.append((x,y,w,h))
-‎    return icons,pos
-‎
-‎
-‎def img_hash(img):
-‎    small=cv2.resize(img,(8,8))
-‎    return (small>small.mean()).astype(np.uint8).flatten()
-‎
-‎
-‎def rare_icon(icons,pos):
-‎    hashes=[img_hash(i) for i in icons]
-‎    groups=[]
-‎
-‎    for h in hashes:
-‎        placed=False
-‎        for g in groups:
-‎            if np.sum(h!=g[0]) < 4:
-‎                g.append(h); placed=True; break
-‎        if not placed:
-‎            groups.append([h])
-‎
-‎    rare=min(groups,key=len)[0]
-‎    idx=[h.tolist()==rare.tolist() for h in hashes].index(True)
-‎    x,y,w,h = pos[idx]
-‎    return x+w//2, y+h//2, (x,y,w,h)
-‎
-‎
-‎@app.post("/solve")
-‎def solve(req:SolveRequest):
-‎
-‎    img = b64_to_image(req.image_base64)
-‎    icons,pos = extract_icons(img)
-‎    cx,cy,(bx,by,bw,bh) = rare_icon(icons,pos)
-‎
-‎    cv2.rectangle(img,(bx,by),(bx+bw,by+bh),(0,0,255),3)
-‎    cv2.circle(img,(cx,cy),8,(0,0,255),-1)
-‎
-‎    _,buf=cv2.imencode(".png",img)
-‎    result_b64=base64.b64encode(buf).decode()
-‎
-‎    return {
-‎        "widgetId":req.widgetId,
-‎        "challengeId":req.challengeId,
-‎        "click_x":cx,
-‎        "click_y":cy,
-‎        "result_base64":result_b64
-‎    }
-‎
-‎
-‎def start():
-‎    uvicorn.run(app,host="0.0.0.0",port=7860)
-‎
-‎if __name__=="__main__":
-‎    start()
-‎
+from fastapi import FastAPI
+from pydantic import BaseModel
+import uvicorn
+
+app = FastAPI(
+    title="IconCaptcha Solver API",
+    version="1.0",
+    description="Solver IconCaptcha - return click point, bounding box, and edited image"
+)
+
+class SolveRequest(BaseModel):
+    widgetId: str
+    challengeId: str
+    image_base64: str
+
+
+def b64_to_image(b64):
+    nparr = np.frombuffer(base64.b64decode(b64), np.uint8)
+    img = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
+
+    if img.shape[2] == 4:   # transparan → ubah ke background putih
+        alpha = img[:,:,3] / 255.0
+        rgb   = img[:,:,:3]
+        bg    = np.ones_like(rgb)*255
+        img   = (rgb*alpha[:,:,None] + bg*(1-alpha[:,:,None])).astype(np.uint8)
+
+    return img
+
+
+def extract_icons(img):
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    _,thr = cv2.threshold(gray,200,255,cv2.THRESH_BINARY_INV)
+    cnt,_ = cv2.findContours(thr,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+
+    icons,pos=[],[]
+    for c in cnt:
+        x,y,w,h=cv2.boundingRect(c)
+        if w>20 and h>20:
+            roi=cv2.resize(thr[y:y+h,x:x+w],(50,50))
+            icons.append(roi)
+            pos.append((x,y,w,h))
+    return icons,pos
+
+
+def img_hash(img):
+    small=cv2.resize(img,(8,8))
+    return (small>small.mean()).astype(np.uint8).flatten()
+
+
+def rare_icon(icons,pos):
+    hashes=[img_hash(i) for i in icons]
+    groups=[]
+
+    for h in hashes:
+        placed=False
+        for g in groups:
+            if np.sum(h!=g[0]) < 4:
+                g.append(h); placed=True; break
+        if not placed:
+            groups.append([h])
+
+    rare=min(groups,key=len)[0]
+    idx=[h.tolist()==rare.tolist() for h in hashes].index(True)
+    x,y,w,h = pos[idx]
+    return x+w//2, y+h//2, (x,y,w,h)
+
+
+@app.post("/solve")
+def solve(req:SolveRequest):
+
+    img = b64_to_image(req.image_base64)
+    icons,pos = extract_icons(img)
+    cx,cy,(bx,by,bw,bh) = rare_icon(icons,pos)
+
+    cv2.rectangle(img,(bx,by),(bx+bw,by+bh),(0,0,255),3)
+    cv2.circle(img,(cx,cy),8,(0,0,255),-1)
+
+    _,buf=cv2.imencode(".png",img)
+    result_b64=base64.b64encode(buf).decode()
+
+    return {
+        "widgetId":req.widgetId,
+        "challengeId":req.challengeId,
+        "click_x":cx,
+        "click_y":cy,
+        "result_base64":result_b64
+    }
+
+
+def start():
+    uvicorn.run(app,host="0.0.0.0",port=7860)
+
+if __name__=="__main__":
+    start()