Update API handler

app.py

@@ -303,15 +303,16 @@ def stream(uid:str):
 # ─── Detect animal/wildlife ─────────────────────────────────────────────────
 # Init clients
 # https://universe.roboflow.com/team-hope-mmcyy/hydroquest
-robo_fish = InferenceHTTPClient(
-    api_url="https://detect.roboflow.com",
-    api_key=os.getenv("ROBOFLOW_KEY", "")
-)
-# https://universe.roboflow.com/sky-sd2zq/bird_only-pt0bm/model/1
-robo_bird = InferenceHTTPClient(
-    api_url="https://detect.roboflow.com",
-    api_key=os.getenv("ROBOFLOW_KEY", "")
-)
+import base64, requests
+def roboflow_infer(image_path, api_url, api_key):
+    with open(image_path, "rb") as f:
+        img_b64 = base64.b64encode(f.read()).decode()
+    res = requests.post(api_url, json={
+        "api_key": api_key,
+        "image": img_b64
+    }, headers={"Content-Type": "application/json"})
+    return res.json()
+
 # Animal detection endpoint (animal, fish, bird as target classes)
 @app.post("/animal/")
 async def detect_animals(file: UploadFile = File(...)):
@@ -342,8 +343,12 @@ async def detect_animals(file: UploadFile = File(...)):
     # 2. Roboflow Fish
     try:
         print("[Animal] Detecting via Roboflow Fish model…")
-        fish_preds = robo_fish.infer(img_path, model_id="hydroquest/1")
-        for pred in fish_preds.get("predictions", []):
+        fish_response = roboflow_infer(
+            img_path,
+            "https://detect.roboflow.com/hydroquest/1",
+            api_url=os.getenv("ROBOFLOW_KEY", "")
+        )
+        for pred in fish_response.get("predictions", []):
             if pred["confidence"] >= 0.75:
                 x1 = int(pred["x"] - pred["width"] / 2)
                 y1 = int(pred["y"] - pred["height"] / 2)
@@ -356,8 +361,12 @@ async def detect_animals(file: UploadFile = File(...)):
     # 3. Roboflow Bird
     try:
         print("[Animal] Detecting via Roboflow Bird model…")
-        bird_preds = robo_bird.infer(img_path, model_id="bird_only-pt0bm/1")
-        for pred in bird_preds.get("predictions", []):
+        bird_response = roboflow_infer(
+            img_path,
+            "https://detect.roboflow.com/bird_only-pt0bm/1",
+            api_url=os.getenv("ROBOFLOW_KEY", "")
+        )
+        for pred in bird_response.get("predictions", []):
             if pred["confidence"] >= 0.75:
                 x1 = int(pred["x"] - pred["width"] / 2)
                 y1 = int(pred["y"] - pred["height"] / 2)
@@ -366,6 +375,7 @@ async def detect_animals(file: UploadFile = File(...)):
                 detections.append(((x1, y1, x2, y2), "Bird Alert"))
     except Exception as e:
         print("[Roboflow Bird Error]", e)
+
     # Count detection
     print(f"[Animal] Total detections: {len(detections)}")
     # Write label