corrigiendo app

app.py

@@ -3,11 +3,14 @@ from typing import Optional, List
 import numpy as np, cv2, torch
 from ultralytics import YOLO
 import easyocr
+from PIL import Image
+import pillow_heif
 
 from fastapi import FastAPI, HTTPException, File, UploadFile, Form
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel, Field
 
+
 TMP_DIR = "/tmp"
 paths = [
     f"{TMP_DIR}/Ultralytics",
@@ -119,25 +122,42 @@ def bgr_to_jpeg_base64(bgr):
         return None
     return base64.b64encode(buf.tobytes()).decode("ascii")
 
-def load_image_from_url(url: str):
-    ssl._create_default_https_context = ssl._create_unverified_context
-    data = urllib.request.urlopen(url).read()
+def pil_to_bgr(pil_img: Image.Image) -> np.ndarray:
+    if pil_img.mode not in ("RGB", "RGBA"):
+        pil_img = pil_img.convert("RGB")
+    arr = np.array(pil_img)
+    if arr.ndim == 2:
+        arr = np.stack([arr]*3, axis=-1)
+    if arr.shape[2] == 4:
+        arr = arr[:, :, :3]
+    return cv2.cvtColor(arr, cv2.COLOR_RGB2BGR)
+
+def decode_bytes_to_bgr(data: bytes, content_type: str = "") -> np.ndarray:
+    # 1) OpenCV rápido
     arr = np.frombuffer(data, np.uint8)
     bgr = cv2.imdecode(arr, cv2.IMREAD_COLOR)
-    if bgr is None:
-        raise ValueError("No pude decodificar la imagen desde URL.")
-    return bgr
+    if bgr is not None:
+        return bgr
+    # 2) Fallback PIL (con HEIC soportado por pillow-heif)
+    try:
+        with Image.open(io.BytesIO(data)) as im:
+            return pil_to_bgr(im)
+    except Exception as e:
+        raise ValueError(f"No pude decodificar la imagen ({content_type}): {e}")
 
-def load_image_from_b64(b64_or_data_url: str):
+def load_image_from_url(url: str) -> np.ndarray:
+    ssl._create_default_https_context = ssl._create_unverified_context
+    req = urllib.request.Request(url, headers={"User-Agent": "Mozilla/5.0"})
+    with urllib.request.urlopen(req, timeout=20) as r:
+        data = r.read()
+    return decode_bytes_to_bgr(data, content_type=r.headers.get("Content-Type",""))
+
+def load_image_from_b64(b64_or_data_url: str) -> np.ndarray:
     s = b64_or_data_url
     if s.startswith("data:"):
         s = s.split(",", 1)[1]
     raw = base64.b64decode(s)
-    arr = np.frombuffer(raw, np.uint8)
-    bgr = cv2.imdecode(arr, cv2.IMREAD_COLOR)
-    if bgr is None:
-        raise ValueError("No pude decodificar la imagen desde base64.")
-    return bgr
+    return decode_bytes_to_bgr(raw, content_type="base64")
 
 # --- FastAPI ---
 app = FastAPI(title="Plates API (HF Space)")
@@ -192,6 +212,7 @@ def detect(req: DetectRequest):
     try:
         if not req.image_url and not req.image_b64:
             raise HTTPException(400, "Proporciona 'image_url' o 'image_b64'.")
+
         bgr = load_image_from_url(req.image_url) if req.image_url else load_image_from_b64(req.image_b64)
         vis, dets, (w, h), dt_ms = run_on_image_bgr(
             bgr, conf=req.conf, iou=req.iou, with_ocr=req.ocr, annotate=req.return_image
@@ -219,10 +240,9 @@ async def detect_upload(
         if not data:
             raise HTTPException(400, "Archivo vacío.")
 
-        arr = np.frombuffer(data, np.uint8)
-        bgr = cv2.imdecode(arr, cv2.IMREAD_COLOR)
+        bgr = decode_bytes_to_bgr(data, content_type=image.content_type or image.filename)
         if bgr is None:
-            # mejor devolver 415 que 500 si no se puede decodificar (HEIC, dañada, etc.)
+            # si llega aquí es que ni cv2 ni PIL pudieron
             raise HTTPException(415, f"Formato no soportado: {image.content_type or image.filename}")
 
         vis, dets, (w, h), dt_ms = run_on_image_bgr(
@@ -236,7 +256,6 @@ async def detect_upload(
     except HTTPException:
         raise
     except Exception as e:
-        # esto hará que tu front vea el mensaje real en data.detail
         raise HTTPException(500, f"Error procesando la imagen: {e}")
 
 @app.on_event("startup")

requirements.txt

@@ -8,3 +8,5 @@ easyocr
 opencv-python==4.10.0.84
 huggingface_hub
 torch
+pillow
+pillow-heif