Перенес networks внутрь src

interpolator.py

@@ -4,8 +4,8 @@ from pathlib import Path
 import torch
 import numpy as np
 from omegaconf import OmegaConf, DictConfig
+from imageio import imread, imwrite
 
-from src.utils import utils
 from src.utils.torch import img2tensor, check_dim_and_resize, tensor2img
 from src.utils.build import build_from_cfg
 from src.utils.padder import InputPadder
@@ -84,9 +84,16 @@ class ImageInterpolator:
         )
 
     def interpolate(self, image1: Path, image2: Path, output_path: Path):
+        """
+        Interpolates between two images and saves the result.
+        Args:
+            image1 (Path): Path to the first input image (only png and jpg formats are supported)
+            image2 (Path): Path to the second input image (only png and jpg formats are supported)
+            output_path (Path): Path to save the interpolated image (only png and jpg formats are supported)
+        """
         logging.debug(f"Reading images: {image1} and {image2}")
-        tensor1 = img2tensor(utils.read(image1)).to(self.device)
-        tensor2 = img2tensor(utils.read(image2)).to(self.device)
+        tensor1 = img2tensor(imread(image1)).to(self.device)
+        tensor2 = img2tensor(imread(image2)).to(self.device)
         logging.debug(
             f"Image shapes after conversion to tensors: {tensor1.shape}, {tensor2.shape}"
         )
@@ -115,7 +122,7 @@ class ImageInterpolator:
         logging.debug(f"Interpolated image shape before unpadding: {interpolated.shape}")
         (interpolated,) = padder.unpad(interpolated)
         logging.debug(f"Interpolated image shape after unpadding: {interpolated.shape}")
-        utils.write(output_path, tensor2img(interpolated.cpu()))
+        imwrite(output_path, tensor2img(interpolated.cpu()))
         logging.debug(f"Saved interpolated image to: {output_path}")
 
     def scale(self, height: int, width: int) -> float: