Segmentantor

bash scripts/download_sam.sh

docker compose up -d

curl -X POST http://localhost:8090/segment \
  -H "Content-Type: application/json" \
  -d '{"image_url": "/api/gpkg/file.gpkg/tiles/17/1234/5678/", "click_x": 128, "click_y": 100}'

{
  "task_id": "a1b2c3d4e5f6",
  "status": "queued",
  "queue_depth": 0
}

{
  "processors": [
    { "name": "sam", "ready": true, "description": "Segment Anything Model (ViT-B, ONNX quantized)" }
  ],
  "default": "sam"
}

{
  "id": "a1b2c3d4e5f6",
  "created_at_iso": "2026-03-27 18:00:00",
  "processor": "sam",
  "status": "success",
  "duration_ms": 1523.4,
  "result_vertices": 42,
  "result_score": 0.952
}

const ws = new WebSocket('ws://localhost:8090/ws/tasks');
ws.onmessage = (e) => {
  const task = JSON.parse(e.data);
  console.log(`[${task.status}] ${task.id} — ${task.duration_ms?.toFixed(0)}ms`);
};

{
  "tasks": [
    {
      "id": "a1b2c3d4e5f6",
      "created_at_iso": "2026-03-28 12:00:00",
      "processor": "sam",
      "status": "success",
      "duration_ms": 1523.4,
      "result_vertices": 42,
      "result_score": 0.952
    }
  ],
  "total": 128,
  "page": 1,
  "per_page": 50,
  "pages": 3
}

{
  "id": "a1b2c3d4e5f6",
  "status": "success",
  "processor": "sam",
  "duration_ms": 1523.4,
  "result_vertices": 42,
  "result_score": 0.952,
  "result_processor": "sam",
  "contour": [[102.0, 85.0], [115.0, 82.0], ...],
  "mask_width": 256,
  "mask_height": 256,
  "preview_input": "/data/previews/a1b2c3d4e5f6_input.png",
  "preview_result": "/data/previews/a1b2c3d4e5f6_result.png"
}

{
  "enabled_processors": ["sam", "yolo"],
  "use_gpu": false,
  "default_processor": "sam",
  "sam": {
    "embedding_cache_size": 16,
    "simplify_tolerance": 2.0,
    "ort_inter_threads": 2,
    "ort_intra_threads": 4
  },
  "yolo": {
    "conf_threshold": 0.25,
    "iou_threshold": 0.7
  }
}

POST https://your-server.com/callback
Content-Type: application/json
X-Webhook-Signature: sha256=a1b2c3d4...

{
  "id": "a1b2c3d4e5f6",
  "status": "success",
  "processor": "sam",
  "duration_ms": 1523.4,
  "result_vertices": 42,
  "result_score": 0.952,
  "contour": [[102.0, 85.0], [115.0, 82.0], ...],
  "mask_width": 256,
  "mask_height": 256
}

{
  "detail": [
    {
      "type": "value_error",
      "loc": ["body"],
      "msg": "Provide at least one prompt: click_x+click_y, points, or box.",
      "input": {}
    }
  ]
}

models/sam/
├── vision_encoder_quantized.onnx          # ~97 MB
└── prompt_encoder_mask_decoder_quantized.onnx  # ~5 MB

# app/processors/yolo.py
from .base import BaseProcessor, SegmentResult

class YOLOProcessor(BaseProcessor):
    name = 'yolo'
    description = 'YOLOv8 instance segmentation'

    def load(self):
        self._ready = True

    def segment(self, image, points, labels=None, *, cache_key=None):
        return SegmentResult(
            mask=binary_mask,
            score=confidence,
            orig_width=image.shape[1],
            orig_height=image.shape[0],
        )

# app/processors/__init__.py
PROCESSORS = {
    'sam': SAMProcessor(),
    'yolo': YOLOProcessor(),
}

# Собрать и запустить
docker compose up -d

# Или вручную
docker build -t geo_segmentantor .
docker run -d -p 8090:80 geo_segmentantor

models/
├── sam/
│   ├── vision_encoder_quantized.onnx
│   └── prompt_encoder_mask_decoder_quantized.onnx
└── yolo/
    └── model.onnx