Avoid circular dep. issue (maybe better way to do this)

src/mflux/controlnet/controlnet_util.py

@@ -3,9 +3,8 @@ import os
 
 import cv2
 import numpy as np
-import PIL
+import PIL.Image
 
-from mflux import ImageUtil
 
 log = logging.getLogger(__name__)
 
@@ -27,7 +26,9 @@ class ControlnetUtil:
         return img
 
     @staticmethod
-    def save_canny_image(control_image, path: str):
+    def save_canny_image(control_image: PIL.Image, path: str):
+        from mflux import ImageUtil
+
         base, ext = os.path.splitext(path)
         new_filename = f"{base}_controlnet_canny{ext}"
         ImageUtil.save_image(control_image, new_filename)

src/mflux/controlnet/flux_controlnet.py

@@ -1,4 +1,5 @@
 import logging
+from typing import TYPE_CHECKING
 
 import mlx.core as mx
 from mlx import nn
@@ -14,7 +15,6 @@ from mflux.models.text_encoder.clip_encoder.clip_encoder import CLIPEncoder
 from mflux.models.text_encoder.t5_encoder.t5_encoder import T5Encoder
 from mflux.models.transformer.transformer import Transformer
 from mflux.models.vae.vae import VAE
-from mflux.post_processing.generated_image import GeneratedImage
 from mflux.post_processing.image_util import ImageUtil
 from mflux.tokenizer.clip_tokenizer import TokenizerCLIP
 from mflux.tokenizer.t5_tokenizer import TokenizerT5
@@ -22,6 +22,10 @@ from mflux.tokenizer.tokenizer_handler import TokenizerHandler
 from mflux.weights.model_saver import ModelSaver
 from mflux.weights.weight_handler import WeightHandler
 
+if TYPE_CHECKING:
+    from mflux.post_processing.generated_image import GeneratedImage
+
+
 log = logging.getLogger(__name__)
 
 CONTROLNET_ID = "InstantX/FLUX.1-dev-Controlnet-Canny"
@@ -107,7 +111,7 @@ class Flux1Controlnet:
             control_image_path: str,
             save_control_image_canny: bool = False,
             config: ConfigControlnet = ConfigControlnet()
-    ) -> GeneratedImage:  # fmt: off
+    ) -> "GeneratedImage":  # fmt: off
         # Create a new runtime config based on the model type and input parameters
         config = RuntimeConfig(config, self.model_config)
         time_steps = tqdm(range(config.num_inference_steps))

src/mflux/post_processing/generated_image.py

@@ -3,7 +3,6 @@ import importlib
 import PIL.Image
 import mlx.core as mx
 
-from mflux import ImageUtil
 from mflux.config.model_config import ModelConfig
 
 
@@ -39,6 +38,8 @@ class GeneratedImage:
         self.controlnet_strength = controlnet_strength
 
     def save(self, path: str, export_json_metadata: bool = False) -> None:
+        from mflux import ImageUtil
+
         ImageUtil.save_image(self.image, path, self._get_metadata(), export_json_metadata)
 
     def _get_metadata(self) -> dict: