fix typing errors

vision_agent/image_utils.py

@@ -5,16 +5,17 @@
 
 import numpy as np
 from PIL import Image
+from PIL.Image import Image as ImageType
 
 
-def b64_to_pil(b64_str: str) -> Image.Image:
+def b64_to_pil(b64_str: str) -> ImageType:
  # , can't be encoded in b64 data so must be part of prefix
  if "," in b64_str:
  b64_str = b64_str.split(",")[1]
  return Image.open(BytesIO(base64.b64decode(b64_str)))
 
 
-def get_image_size(data: Union[str, Path, np.ndarray, Image.Image]) -> Tuple[int, ...]:
+def get_image_size(data: Union[str, Path, np.ndarray, ImageType]) -> Tuple[int, ...]:
  if isinstance(data, (str, Path)):
  data = Image.open(data)
 
@@ -24,7 +25,7 @@ def get_image_size(data: Union[str, Path, np.ndarray, Image.Image]) -> Tuple[int
  return data.shape[:2]
 
 
-def convert_to_b64(data: Union[str, Path, np.ndarray, Image.Image]) -> str:
+def convert_to_b64(data: Union[str, Path, np.ndarray, ImageType]) -> str:
  if data is None:
  raise ValueError(f"Invalid input image: {data}. Input image can't be None.")
  if isinstance(data, (str, Path)):

vision_agent/llm/llm.py

@@ -1,6 +1,6 @@
 import json
 from abc import ABC, abstractmethod
-from typing import cast
+from typing import Any, Dict, cast
 
 from vision_agent.tools import (
  CHOOSE_PARAMS,
@@ -67,7 +67,7 @@ def generate_detector(self, params: str) -> ImageTool:
  params = json.loads(cast(str, response.choices[0].message.content))[
  "Parameters"
  ]
- return GroundingDINO(**params)
+ return GroundingDINO(*params)
 
  def generate_segmentor(self, params: str) -> ImageTool:
  params = CHOOSE_PARAMS.format(api_doc=GroundingSAM.doc, question=params)
@@ -83,4 +83,4 @@ def generate_segmentor(self, params: str) -> ImageTool:
  params = json.loads(cast(str, response.choices[0].message.content))[
  "Parameters"
  ]
- return GroundingSAM(**params)
+ return GroundingSAM(*params)