AC: update style transfer converter (#3446)

Author: eaidova

tools/accuracy_checker/openvino/tools/accuracy_checker/annotation_converters/README.md

@@ -618,6 +618,7 @@ The main difference between this converter and `super_resolution` in data organi
    * `data_dir` - directory, where input images and annotation files in MATLAB format stored.
 * `style_transfer` - converts images to `StyleTransferAnnotation`.
   * `images_dir` - path to images directory.
+  * `annotation_file` - path to file with annotation in format: `[input_img1] [ref_img]` if you have single input model or `[input_img1] [input_img2] [ref_img]` if you have 2 inputs.
 * `ade20k` - converts ADE20K dataset to `SegmentationAnnotation`.
   * `images_dir` - path to directory with images (e.g. `ADEChallengeData2016/images/validation`).
   * `annotations_dir` - path to directory with annotations (e.g. `ADEChallengeData2016/annotations/validation`).

tools/accuracy_checker/openvino/tools/accuracy_checker/annotation_converters/style_transfer.py

@@ -17,6 +17,7 @@
 from ..config import PathField
 from ..representation import StyleTransferAnnotation
 from .format_converter import BaseFormatConverter, ConverterReturn
+from ..utils import read_txt, check_file_existence
 
 
 class StyleTransferConverter(BaseFormatConverter):
@@ -30,23 +31,62 @@ def parameters(cls):
             'images_dir': PathField(
                 optional=False, is_directory=True,
                 description="Path to directory with images."
-            )
+            ),
+            'annotation_file': PathField(optional=True, description='File with used images declaration')
         })
         return parameters
 
     def configure(self):
         self.image_dir = self.get_value_from_config('images_dir')
+        self.annotation_file = self.get_value_from_config('annotation_file')
 
     def convert(self, check_content=False, progress_callback=None, progress_interval=100, **kwargs):
         content_check_errors = [] if check_content else None
         annotations = []
+        if self.annotation_file:
+            return self._convert_using_annotation(check_content, progress_callback, progress_interval)
         images = [
             im for im in self.image_dir.iterdir()
             if im.name.lower().endswith(('.png', '.jpg', '.jpeg', '.tiff', '.bmp', '.gif'))
         ]
-        for image in images:
+        num_iteration = len(images)
+        for idx, image in enumerate(images):
             identifiers = image.name
             annotation = StyleTransferAnnotation(identifiers, image.name)
             annotations.append(annotation)
+            if progress_callback and idx % progress_interval:
+                progress_callback(idx * 100 / num_iteration)
 
         return ConverterReturn(annotations, None, content_check_errors)
+
+    def _convert_using_annotation(self, check_content=False, progress_callback=None, progress_interval=100):
+        list_images = read_txt(self.annotation_file)
+        num_lines = len(list_images)
+        annotation = []
+        content_errors = [] if check_content else None
+        for line_id, line in enumerate(list_images):
+            data = line.split()
+            if len(data) == 1:
+                identifier = data[0]
+                reference = data[0]
+            elif len(data) == 2:
+                identifier = data[0]
+                reference = data[1]
+            else:
+                identifier = data[:-1]
+                reference = data[-1]
+            if check_content:
+                if isinstance(identifier, str):
+                    if not check_file_existence(self.image_dir / identifier):
+                        content_errors.append(f'{self.image_dir / identifier}: does not exists')
+                else:
+                    for img in identifier:
+                        if not check_file_existence(self.image_dir / img):
+                            content_errors.append(f'{self.image_dir / identifier}: does not exists')
+                if not check_file_existence(self.image_dir / reference):
+                    content_errors.append(f'{self.image_dir/reference}: does not exist')
+            ann = StyleTransferAnnotation(identifier, reference)
+            if progress_callback and line_id % progress_interval:
+                progress_callback(line_id * 100 / num_lines)
+            annotation.append(ann)
+        return ConverterReturn(annotation, None, content_errors)