edit tag

api/detection.py

@@ -1,7 +1,65 @@
+# from fastapi import APIRouter, UploadFile, File, Form, HTTPException
+# from pathlib import Path
+# import cv2
+# import numpy as np
+
+# from .config import UPLOAD_DIR
+# from .utils import (
+#     validate_form,
+#     process_image,
+#     save_image,
+#     load_json,
+#     save_json,
+#     validate_user_and_camera,extract_metadata
+# )
+
+# router = APIRouter()
+# @router.post("/predict")
+# async def predict(
+#     user_id: str = Form(...),
+#     camera_name: str = Form(...),
+#     images: list[UploadFile] = File(...)
+# ):
+#     images = validate_form(user_id, camera_name, images)
+#     validate_user_and_camera(user_id, camera_name)
+#     base = Path(UPLOAD_DIR) / user_id / camera_name
+#     base.mkdir(parents=True, exist_ok=True)     
+#     json_path = base / f"{camera_name}_detections.json"
+#     data = load_json(json_path)
+#     new_results = []
+#     for file in images:
+#         raw = await file.read()
+#         metadata = extract_metadata(raw)
+#         nparr = np.frombuffer(raw, np.uint8)
+#         img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+#         if img is None:
+#             raise HTTPException(400, f"Invalid image: {file.filename}")
+#         detections = process_image(img)
+#         url = save_image(user_id, camera_name, file.filename, raw)
+#         record = {
+#             "filename": file.filename,
+#             "image_url": url,
+#             "detections": detections,
+#             "metadata": metadata   
+#         }
+#         data.append(record)
+#         new_results.append(record)
+#     save_json(json_path, data)
+#     return {
+#         "message": "Images processed successfully",
+#         "camera": camera_name,
+#         "results": new_results
+#     }
+
+
+
 from fastapi import APIRouter, UploadFile, File, Form, HTTPException
+from pydantic import BaseModel
 from pathlib import Path
+from typing import Optional, List
 import cv2
 import numpy as np
+import logging
 
 from .config import UPLOAD_DIR
 from .utils import (
@@ -10,10 +68,15 @@ from .utils import (
     save_image,
     load_json,
     save_json,
-    validate_user_and_camera,extract_metadata
+    validate_user_and_camera,
+    extract_metadata
 )
 
 router = APIRouter()
+logger = logging.getLogger(__name__)
+
+
+# ─── existing endpoint (unchanged) ───────────────────────────────────────────
 @router.post("/predict")
 async def predict(
     user_id: str = Form(...),
@@ -23,7 +86,7 @@ async def predict(
     images = validate_form(user_id, camera_name, images)
     validate_user_and_camera(user_id, camera_name)
     base = Path(UPLOAD_DIR) / user_id / camera_name
-    base.mkdir(parents=True, exist_ok=True)     
+    base.mkdir(parents=True, exist_ok=True)
     json_path = base / f"{camera_name}_detections.json"
     data = load_json(json_path)
     new_results = []
@@ -40,7 +103,7 @@ async def predict(
             "filename": file.filename,
             "image_url": url,
             "detections": detections,
-            "metadata": metadata   
+            "metadata": metadata
         }
         data.append(record)
         new_results.append(record)
@@ -50,3 +113,112 @@ async def predict(
         "camera": camera_name,
         "results": new_results
     }
+
+
+# ─── NEW: request model ───────────────────────────────────────────────────────
+class UpdateDetectionRequest(BaseModel):
+    user_id:          str
+    camera_name:      str
+    image_url:        str                        # used to locate the record
+    detection_index:  int        = 0            # which detection inside the image to edit
+    new_label:        str                        # e.g. "Buck", "Doe", "Unknown"
+    new_bbox:         Optional[List[float]] = None  # [x1,y1,x2,y2] in natural px, or null
+
+
+# ─── NEW: endpoint ────────────────────────────────────────────────────────────
+@router.post("/update_detection")
+async def update_detection(req: UpdateDetectionRequest):
+    """
+    Edit the label and/or bounding box of one detection on an already-processed image.
+    Writes the change back into user_data/<user_id>/<camera_name>/<camera_name>_detections.json
+    """
+
+    # ── 1. First check if user directory exists ─────────────────────────
+    user_path = Path(UPLOAD_DIR) / req.user_id
+    if not user_path.exists() or not user_path.is_dir():
+        raise HTTPException(
+            status_code=404,
+            detail="user not found"
+        )
+
+    # ── 2. Check if camera directory exists ────────────────────────────
+    camera_path = user_path / req.camera_name
+    if not camera_path.exists() or not camera_path.is_dir():
+        raise HTTPException(
+            status_code=404,
+            detail="camera not found"
+        )
+
+    # ── 3. Check if detections JSON file exists ─────────────────────────
+    json_path = camera_path / f"{req.camera_name}_detections.json"
+    if not json_path.exists():
+        raise HTTPException(
+            status_code=404,
+            detail="camera not found"  # Camera ke hisaab se JSON file nahi hai
+        )
+
+    # ── 4. Load the JSON data ───────────────────────────────────────────
+    data = load_json(json_path)
+
+    # ── 5. Find the record by matching the filename ─────────────────────
+    target_filename = req.image_url.split("/")[-1].split("?")[0]
+
+    record = None
+    for item in data:
+        stored = item.get("image_url", item.get("filename", ""))
+        stored_filename = stored.split("/")[-1].split("?")[0]
+        if stored_filename == target_filename:
+            record = item
+            break
+
+    if record is None:
+        raise HTTPException(
+            status_code=404,
+            detail="image not found"
+        )
+
+    # ── 6. Apply the edit ───────────────────────────────────────────────
+    dets = record.get("detections", [])
+
+    if not dets:
+        # Image had zero detections before — create the first one manually
+        record["detections"] = [{
+            "label":           req.new_label,
+            "confidence":      1.0,
+            "bbox":            req.new_bbox or [],
+            "manually_edited": True
+        }]
+
+    elif req.detection_index < len(dets):
+        # Normal case: update the detection at the requested index
+        dets[req.detection_index]["label"]           = req.new_label
+        dets[req.detection_index]["manually_edited"] = True
+        if req.new_bbox is not None:
+            dets[req.detection_index]["bbox"] = req.new_bbox
+
+    else:
+        raise HTTPException(
+            status_code=400,
+            detail=f"detection_index {req.detection_index} is out of range "
+                   f"(image has {len(dets)} detection(s))"
+        )
+
+    # ── 7. Save back ────────────────────────────────────────────────────
+    save_json(json_path, data)
+
+    logger.info(
+        "Detection updated | user=%s camera=%s file=%s idx=%d label=%s bbox=%s",
+        req.user_id, req.camera_name, target_filename,
+        req.detection_index, req.new_label, req.new_bbox
+    )
+
+    return {
+        "success": True,
+        "message": "Detection updated successfully",
+        "updated": {
+            "filename":        target_filename,
+            "detection_index": req.detection_index,
+            "new_label":       req.new_label,
+            "new_bbox":        req.new_bbox,
+        }
+    }

api/main.py

@@ -31,7 +31,7 @@ def create_app() -> FastAPI:
         CORSMiddleware,
         allow_origins=[
             'https://embroiderywala.myshopify.com',
-            'https://www.daleandcompany.com','http://127.0.0.1:8080'
+            'https://www.daleandcompany.com','http://127.0.0.1:8080','https://a8a2-185-134-22-81.ngrok-free.app'
         ],
         allow_credentials=True,
         allow_methods=["*"],