retagging images

api/detection.py

@@ -1,57 +1,6 @@
-# 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 pydantic import BaseModel,validator
 from typing import Optional, List, Literal
 import cv2
 import numpy as np
@@ -67,6 +16,8 @@ from .utils import (
     validate_user_and_camera,
     extract_metadata,
     _bucket_key,
+    _key_exists,
+
 )
 
 router = APIRouter()
@@ -120,128 +71,222 @@ async def predict(
 # Request Models
 # ─────────────────
 
-# class DetectionOperation(BaseModel):
-#     action: Literal["add", "update", "delete"]
-#     detection_index: Optional[int] = None
-#     label: Optional[str] = None
-#     bbox: Optional[List[float]] = None  # [x1, y1, x2, y2]
-
-
-# class MultiUpdateRequest(BaseModel):
-#     user_id: str
-#     camera_name: str
-#     image_url: str
-#     operations: List[DetectionOperation]
-
-
-# # ─────────────────
-# # Endpoint
-# # ─────────────────
-
-# @router.post("/modify_detections")
-# async def modify_detections(req: MultiUpdateRequest):
-#     """
-#     Add, update, and delete detections (tags) for a given image.
-#     Supports multiple operations in a single request.
-#     """
-
-#     #  Validate user 
-#     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")
-
-#     #  Validate camera
-#     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")
-
-#     # Validate JSON file
-#     json_path = camera_path / f"{req.camera_name}_detections.json"
-#     if not json_path.exists():
-#         raise HTTPException(status_code=404, detail="detections file not found")
-
-#     #  Load data 
-#     data = load_json(json_path)
-
-#     #  Find image record
-#     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. Ensure detections list exists 
-#     if "detections" not in record or not isinstance(record["detections"], list):
-#         record["detections"] = []
-
-#     dets = record["detections"]
-
-#     # ── 7. Apply operations safely ──────
-#     # NOTE: Reverse delete operations to avoid index shifting issues
-#     delete_ops = [op for op in req.operations if op.action == "delete"]
-#     other_ops = [op for op in req.operations if op.action != "delete"]
-
-#     #  Handle DELETE (reverse order)
-#     for op in sorted(delete_ops, key=lambda x: x.detection_index or -1, reverse=True):
-#         if op.detection_index is None or op.detection_index >= len(dets):
-#             raise HTTPException(
-#                 status_code=400,
-#                 detail=f"Invalid delete index {op.detection_index}"
-#             )
-#         dets.pop(op.detection_index)
-
-#     #  Handle ADD + UPDATE
-#     for op in other_ops:
-
-#         #  ADD
-#         if op.action == "add":
-#             dets.append({
-#                 "label": op.label or "Unknown",
-#                 "confidence": 1.0,
-#                 "bbox": op.bbox or [],
-#                 "manually_edited": True
-#             })
-
-#         #  UPDATE
-#         elif op.action == "update":
-#             if op.detection_index is None or op.detection_index >= len(dets):
-#                 raise HTTPException(
-#                     status_code=400,
-#                     detail=f"Invalid update index {op.detection_index}"
-#                 )
-
-#             if op.label is not None:
-#                 dets[op.detection_index]["label"] = op.label
-
-#             if op.bbox is not None:
-#                 dets[op.detection_index]["bbox"] = op.bbox
-
-#             dets[op.detection_index]["manually_edited"] = True
-
-#     # ── 8. Save back ────────────────────
-#     save_json(json_path, data)
-
-#     logger.info(
-#         "Detections modified | user=%s camera=%s file=%s ops=%d final_count=%d",
-#         req.user_id,
-#         req.camera_name,
-#         target_filename,
-#         len(req.operations),
-#         len(dets)
-#     )
-
-#     # ── 9. Response ─────────────────────
-#     return {
-#         "success": True,
-#         "message": "Detections modified successfully",
-#         "filename": target_filename,
-#         "total_detections": len(dets),
-#         "detections": dets
-#     }
+ 
+# ================================================================
+# VALID LABELS  —  must exactly match what process_images_batch()
+# produces from the 3-stage YOLO pipeline:
+#   Stage 1: deer detected
+#   Stage 2: Buck  →  Stage 3: Whitetail | Mule
+#   Stage 2: Doe
+# ================================================================
+VALID_LABELS = {
+    "Deer | Doe ",               # trailing space matches pipeline output
+    "Deer | Buck | Whitetail",
+    "Deer | Buck | Mule",
+}
+ 
+VALID_LABELS_DISPLAY = [        # clean version shown in error messages
+    "Deer | Doe",
+    "Deer | Buck | Whitetail",
+    "Deer | Buck | Mule",
+]
+ 
+ 
+def _normalise_label(label: str) -> str:
+    """Strip and normalise label so 'Deer | Doe' == 'Deer | Doe '."""
+    return label.strip()
+ 
+ 
+def _validate_label(label: str) -> str:
+    """Raise a clear error if the label is not from the detection pipeline."""
+    normalised = _normalise_label(label)
+    # Match against normalised versions of VALID_LABELS
+    if normalised not in {l.strip() for l in VALID_LABELS}:
+        raise HTTPException(
+            status_code=422,
+            detail=(
+                f"Invalid label '{label}'. "
+                f"Must be one of: {VALID_LABELS_DISPLAY}"
+            )
+        )
+    # Return the canonical pipeline form (with trailing space for Doe)
+    for valid in VALID_LABELS:
+        if valid.strip() == normalised:
+            return valid
+    return label
+ 
+ 
+# ─────────────────
+# Request Models
+# ─────────────────
+ 
+class DetectionOperation(BaseModel):
+    action: Literal["add", "update", "delete"]
+    detection_index: Optional[int] = None
+    label: Optional[str] = None
+    bbox: Optional[List[float]] = None   # [x1, y1, x2, y2]
+ 
+    @validator("label")
+    def label_must_be_valid(cls, v):
+        if v is None:
+            return v
+        normalised = v.strip()
+        valid_normalised = {l.strip() for l in VALID_LABELS}
+        if normalised not in valid_normalised:
+            raise ValueError(
+                f"Invalid label '{v}'. Must be one of: {VALID_LABELS_DISPLAY}"
+            )
+        # Return canonical form
+        for valid in VALID_LABELS:
+            if valid.strip() == normalised:
+                return valid
+        return v
+ 
+    @validator("bbox")
+    def bbox_must_be_four_values(cls, v):
+        if v is None:
+            return v
+        if len(v) != 4:
+            raise ValueError("bbox must have exactly 4 values: [x1, y1, x2, y2]")
+        x1, y1, x2, y2 = v
+        if x2 <= x1 or y2 <= y1:
+            raise ValueError("bbox must satisfy x2 > x1 and y2 > y1")
+        return v
+ 
+    @validator("detection_index")
+    def index_must_be_non_negative(cls, v):
+        if v is not None and v < 0:
+            raise ValueError("detection_index must be >= 0")
+        return v
+ 
+ 
+class MultiUpdateRequest(BaseModel):
+    user_id: str
+    camera_name: str
+    image_url: str
+    operations: List[DetectionOperation]
+ 
+    @validator("operations")
+    def operations_must_not_be_empty(cls, v):
+        if not v:
+            raise ValueError("operations list cannot be empty")
+        return v
+ 
+    @validator("operations", each_item=True)
+    def validate_operation_fields(cls, op):
+        if op.action == "add":
+            if op.label is None:
+                raise ValueError("'add' operation requires a label")
+            if op.bbox is None:
+                raise ValueError("'add' operation requires a bbox")
+        elif op.action == "update":
+            if op.detection_index is None:
+                raise ValueError("'update' operation requires detection_index")
+            if op.label is None and op.bbox is None:
+                raise ValueError("'update' operation requires at least label or bbox")
+        elif op.action == "delete":
+            if op.detection_index is None:
+                raise ValueError("'delete' operation requires detection_index")
+        return op
+ 
+ 
+# ─────────────────
+# Endpoint
+# ─────────────────
+ 
+@router.post("/modify_detections")
+async def modify_detections(req: MultiUpdateRequest):
+    """
+    Add, update, and delete detections (tags) for a given image.
+    Supports multiple operations in a single request.
+    Labels must match the detection pipeline format exactly.
+    """
+ 
+    # ── Validate user & camera ────────────────────────────────────
+    validate_user_and_camera(req.user_id, req.camera_name)
+ 
+    # ── Validate detections JSON exists in bucket ─────────────────
+    json_key = _bucket_key(req.user_id, req.camera_name, f"{req.camera_name}_detections.json")
+    if not _key_exists(json_key):
+        raise HTTPException(status_code=404, detail="Detections file not found")
+ 
+    # ── Load data from bucket ─────────────────────────────────────
+    data = load_json(json_key)
+ 
+    # ── Find image record by 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")
+ 
+    # ── Ensure detections list exists ─────────────────────────────
+    if "detections" not in record or not isinstance(record["detections"], list):
+        record["detections"] = []
+ 
+    dets = record["detections"]
+ 
+    # ── Apply operations ──────────────────────────────────────────
+    # Deletes run in reverse index order to avoid index shifting
+    delete_ops = [op for op in req.operations if op.action == "delete"]
+    other_ops  = [op for op in req.operations if op.action != "delete"]
+ 
+    # DELETE (reverse order to avoid index shifting)
+    for op in sorted(delete_ops, key=lambda x: x.detection_index or -1, reverse=True):
+        if op.detection_index >= len(dets):
+            raise HTTPException(
+                status_code=400,
+                detail=f"Invalid delete index {op.detection_index} — only {len(dets)} detection(s) exist"
+            )
+        dets.pop(op.detection_index)
+ 
+    # ADD + UPDATE
+    for op in other_ops:
+ 
+        if op.action == "add":
+            dets.append({
+                "label":           op.label,   # already validated & canonicalised by validator
+                "confidence":      1.0,
+                "bbox":            op.bbox,
+                "manually_edited": True
+            })
+ 
+        elif op.action == "update":
+            if op.detection_index >= len(dets):
+                raise HTTPException(
+                    status_code=400,
+                    detail=f"Invalid update index {op.detection_index} — only {len(dets)} detection(s) exist"
+                )
+            if op.label is not None:
+                dets[op.detection_index]["label"] = op.label
+            if op.bbox is not None:
+                dets[op.detection_index]["bbox"] = op.bbox
+            dets[op.detection_index]["manually_edited"] = True
+ 
+    # ── Save back to bucket ───────────────────────────────────────
+    save_json(json_key, data)
+ 
+    logger.info(
+        "Detections modified | user=%s camera=%s file=%s ops=%d final_count=%d",
+        req.user_id,
+        req.camera_name,
+        target_filename,
+        len(req.operations),
+        len(dets)
+    )
+ 
+    return {
+        "success":          True,
+        "message":          "Detections modified successfully",
+        "filename":         target_filename,
+        "total_detections": len(dets),
+        "detections":       dets
+    }
+