Add Deepstack/CodeProject-AI.Server detector plugin (#6143)

* Add Deepstack detector plugin with configurable API URL, timeout, and API key * Update DeepStack plugin to recognize 'truck' as 'car' for label indexing * Add debug logging to DeepStack plugin for better monitoring and troubleshooting * Refactor DeepStack label loading from file to use merged labelmap * Black format * add documentation draft * fix link to codeproject website * Apply suggestions from code review Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2025-10-13 04:23:47 +08:00 · 2023-05-05 02:06:07 +03:00
parent 0751358e5b
commit ede1dedbbd
2 changed files with 100 additions and 0 deletions
--- a/frigate/detectors/plugins/deepstack.py
+++ b/frigate/detectors/plugins/deepstack.py
@@ -0,0 +1,78 @@
+import logging
+import numpy as np
+import requests
+import io
+
+from frigate.detectors.detection_api import DetectionApi
+from frigate.detectors.detector_config import BaseDetectorConfig
+from typing import Literal
+from pydantic import Extra, Field
+from PIL import Image
+
+
+logger = logging.getLogger(__name__)
+
+DETECTOR_KEY = "deepstack"
+
+
+class DeepstackDetectorConfig(BaseDetectorConfig):
+    type: Literal[DETECTOR_KEY]
+    api_url: str = Field(
+        default="http://localhost:80/v1/vision/detection", title="DeepStack API URL"
+    )
+    api_timeout: float = Field(default=0.1, title="DeepStack API timeout (in seconds)")
+    api_key: str = Field(default="", title="DeepStack API key (if required)")
+
+
+class DeepStack(DetectionApi):
+    type_key = DETECTOR_KEY
+
+    def __init__(self, detector_config: DeepstackDetectorConfig):
+        self.api_url = detector_config.api_url
+        self.api_timeout = detector_config.api_timeout
+        self.api_key = detector_config.api_key
+        self.labels = detector_config.model.merged_labelmap
+
+        self.h = detector_config.model.height
+        self.w = detector_config.model.width
+
+    def get_label_index(self, label_value):
+        if label_value.lower() == "truck":
+            label_value = "car"
+        for index, value in self.labels.items():
+            if value == label_value.lower():
+                return index
+        return -1
+
+    def detect_raw(self, tensor_input):
+        image_data = np.squeeze(tensor_input).astype(np.uint8)
+        image = Image.fromarray(image_data)
+        with io.BytesIO() as output:
+            image.save(output, format="JPEG")
+            image_bytes = output.getvalue()
+        data = {"api_key": self.api_key}
+        response = requests.post(
+            self.api_url, files={"image": image_bytes}, timeout=self.api_timeout
+        )
+        response_json = response.json()
+        detections = np.zeros((20, 6), np.float32)
+
+        for i, detection in enumerate(response_json["predictions"]):
+            logger.debug(f"Response: {detection}")
+            if detection["confidence"] < 0.4:
+                logger.debug(f"Break due to confidence < 0.4")
+                break
+            label = self.get_label_index(detection["label"])
+            if label < 0:
+                logger.debug(f"Break due to unknown label")
+                break
+            detections[i] = [
+                label,
+                float(detection["confidence"]),
+                detection["y_min"] / self.h,
+                detection["x_min"] / self.w,
+                detection["y_max"] / self.h,
+                detection["x_max"] / self.w,
+            ]
+
+        return detections