first version

files/client_example.py

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+"""
+Example client: how your annotation tool calls the SAM 3 server.
+
+Run the server first:
+    python sam3_server.py --host 0.0.0.0 --port 8000
+
+Then, from your annotation tool, POST an image + bbox and render the mask.
+"""
+
+import base64
+import io
+import requests
+from PIL import Image
+
+SERVER = "http://localhost:8000"
+
+
+def segment_with_bbox(image_path: str, bbox_xyxy: list[float]):
+    with open(image_path, "rb") as f:
+        img_b64 = base64.b64encode(f.read()).decode("ascii")
+
+    r = requests.post(
+        f"{SERVER}/segment/box",
+        json={
+            "image": img_b64,
+            "bbox": bbox_xyxy,                # [x1, y1, x2, y2] in pixels
+            "multimask_output": False,
+            "return_polygon": True,           # get contour for polygon-based annotation
+            "return_rle": True,               # get COCO RLE for COCO-format export
+        },
+        timeout=60,
+    )
+    r.raise_for_status()
+    data = r.json()
+
+    # Decode mask (single-channel PNG, 0 or 255)
+    mask_png = base64.b64decode(data["mask"])
+    mask = Image.open(io.BytesIO(mask_png))
+    mask.save("mask_out.png")
+
+    print(f"score:   {data['score']:.3f}")
+    print(f"bbox:    {data['bbox_out']}")
+    print(f"polygon: {len(data['polygon']) if data['polygon'] else 0} points")
+    print(f"rle:     size={data['rle']['size']} (counts length={len(str(data['rle']['counts']))})")
+    return data
+
+
+if __name__ == "__main__":
+    # Example: segment the object inside this bbox
+    segment_with_bbox("example.jpg", [120, 80, 540, 420])