add dinov with updated endpoint

vision_agent/tools/tools.py

@@ -389,8 +389,6 @@ class DINOv(Tool):
  [1, 1, 1, ..., 1, 1, 1]], dtype=uint8)]}]
  """
 
- _ENDPOINT = "https://rkgkjvqgh7vbzjdb23tr7eay4a0vczdo.lambda-url.us-east-2.on.aws"
-
  name = "dinov_"
  description = "'dinov_' is a tool that can detect and segment similar objects given a reference segmentation mask."
  usage = {
@@ -437,31 +435,36 @@ def __call__(
  for p in prompt:
  p["mask"] = convert_to_b64(p["mask"])
  p["image"] = convert_to_b64(p["image"])
- data = {
+ request_data = {
  "prompt": prompt,
  "image": image_b64,
+ "tool": "dinov",
  }
- res = requests.post(
- self._ENDPOINT,
- headers={"Content-Type": "application/json"},
- json=data,
- )
- resp_json: Dict[str, Any] = res.json()
- if (
- "statusCode" in resp_json and resp_json["statusCode"] != 200
- ) or "statusCode" not in resp_json:
- _LOGGER.error(f"Request failed: {resp_json}")
- raise ValueError(f"Request failed: {resp_json}")
- rets = resp_json["data"]
- shape = rets.pop("mask_shape")
+ data: Dict[str, Any] = _send_inference_request(request_data, "dinov")
+ if "bboxes" in data:
+ data["bboxes"] = [normalize_bbox(box, data["mask_shape"]) for box in data["bboxes"]]
+ if "masks" in data:
+ data["masks"] = [
+ rle_decode(mask_rle=mask, shape=data["mask_shape"]) for mask in data["masks"]
+ ]
+ data["labels"] = ["visual prompt" for _ in range(len(data["masks"]))]
+ return data
+
+
+class AgentDINOv(DINOv):
+ def __call__(
+ self,
+ prompt: List[Dict[str, str]],
+ image: Union[str, ImageType],
+ ) -> Dict:
+ rets = super().__call__(prompt, image)
  mask_files = []
- for encoded_mask in rets["masks"]:
- mask = rle_decode(mask_rle=encoded_mask, shape=shape)
+ for mask in rets["masks"]:
  with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
- Image.fromarray(mask * 255).save(tmp)
- mask_files.append(tmp.name)
+ file_name = Path(tmp.name).with_suffix(".mask.png")
+ Image.fromarray(mask * 255).save(file_name)
+ mask_files.append(str(file_name))
  rets["masks"] = mask_files
- rets["labels"] = ["visual prompt" for _ in range(len(mask_files))]
  return rets
 
 
@@ -745,6 +748,7 @@ def __call__(self, equation: str) -> float:
  ImageCaption,
  GroundingDINO,
  AgentGroundingSAM,
+ AgentDINOv,
  ExtractFrames,
  Crop,
  BboxArea,