phase cv 0

detect/inference/client.py

@@ -16,7 +16,7 @@ import numpy as np
 import requests
 from PIL import Image
 
-from .types import DetectResult, OCRResult, ServerStatus, VLMResult
+from .types import DetectResult, OCRResult, RegionDebugResult, RegionResult, ServerStatus, VLMResult
 
 logger = logging.getLogger(__name__)
 
@@ -145,6 +145,92 @@ class InferenceClient:
             reasoning=data.get("reasoning", ""),
         )
 
+    def detect_edges(
+        self,
+        image: np.ndarray,
+        edge_canny_low: int = 50,
+        edge_canny_high: int = 150,
+        edge_hough_threshold: int = 80,
+        edge_hough_min_length: int = 100,
+        edge_hough_max_gap: int = 10,
+        edge_pair_max_distance: int = 200,
+        edge_pair_min_distance: int = 15,
+    ) -> list[RegionResult]:
+        """Run edge detection on an image."""
+        payload = {
+            "image": _encode_image(image),
+            "edge_canny_low": edge_canny_low,
+            "edge_canny_high": edge_canny_high,
+            "edge_hough_threshold": edge_hough_threshold,
+            "edge_hough_min_length": edge_hough_min_length,
+            "edge_hough_max_gap": edge_hough_max_gap,
+            "edge_pair_max_distance": edge_pair_max_distance,
+            "edge_pair_min_distance": edge_pair_min_distance,
+        }
+
+        resp = self.session.post(
+            f"{self.base_url}/detect_edges",
+            json=payload,
+            timeout=self.timeout,
+        )
+        resp.raise_for_status()
+
+        results = []
+        for r in resp.json().get("regions", []):
+            result = RegionResult(
+                x=r["x"], y=r["y"], w=r["w"], h=r["h"],
+                confidence=r["confidence"], label=r["label"],
+            )
+            results.append(result)
+        return results
+
+    def detect_edges_debug(
+        self,
+        image: np.ndarray,
+        edge_canny_low: int = 50,
+        edge_canny_high: int = 150,
+        edge_hough_threshold: int = 80,
+        edge_hough_min_length: int = 100,
+        edge_hough_max_gap: int = 10,
+        edge_pair_max_distance: int = 200,
+        edge_pair_min_distance: int = 15,
+    ) -> RegionDebugResult:
+        """Run edge detection with debug overlays."""
+        payload = {
+            "image": _encode_image(image),
+            "edge_canny_low": edge_canny_low,
+            "edge_canny_high": edge_canny_high,
+            "edge_hough_threshold": edge_hough_threshold,
+            "edge_hough_min_length": edge_hough_min_length,
+            "edge_hough_max_gap": edge_hough_max_gap,
+            "edge_pair_max_distance": edge_pair_max_distance,
+            "edge_pair_min_distance": edge_pair_min_distance,
+        }
+
+        resp = self.session.post(
+            f"{self.base_url}/detect_edges/debug",
+            json=payload,
+            timeout=self.timeout,
+        )
+        resp.raise_for_status()
+
+        data = resp.json()
+        regions = []
+        for r in data.get("regions", []):
+            region = RegionResult(
+                x=r["x"], y=r["y"], w=r["w"], h=r["h"],
+                confidence=r["confidence"], label=r["label"],
+            )
+            regions.append(region)
+
+        return RegionDebugResult(
+            regions=regions,
+            edge_overlay_b64=data.get("edge_overlay_b64", ""),
+            lines_overlay_b64=data.get("lines_overlay_b64", ""),
+            horizontal_count=data.get("horizontal_count", 0),
+            pair_count=data.get("pair_count", 0),
+        )
+
     def load_model(self, model: str, quantization: str = "fp16") -> None:
         """Request the server to load a model into VRAM."""
         self.session.post(