chore: code cleanup

modules/metadata.py

@@ -1,12 +1,10 @@
 import json
 import re
-from pathlib import Path
 from abc import ABC, abstractmethod
+from pathlib import Path
 from PIL import Image
 
 import modules.config
-import fooocus_version
-# import advanced_parameters
 from modules.flags import MetadataScheme, Performance, Steps, lora_count_with_lcm
 from modules.util import quote, unquote, extract_styles_from_prompt, is_json, calculate_sha256
 
@@ -30,7 +28,6 @@ class MetadataParser(ABC):
     def parse_json(self, metadata: dict) -> dict:
         raise NotImplementedError
 
-    # TODO add data to parse
     @abstractmethod
     def parse_string(self, metadata: dict) -> str:
         raise NotImplementedError
@@ -219,84 +216,6 @@ class FooocusMetadataParser(MetadataParser):
                 metadata[li] = (label, key, value, show_in_log, copy_in_log)
 
         return json.dumps({k: v for _, k, v, _, _ in metadata})
-        # metadata = {
-        #     # prompt with wildcards
-        #     'prompt': raw_prompt, 'negative_prompt': raw_negative_prompt,
-        #     # prompt with resolved wildcards
-        #     'real_prompt': task['log_positive_prompt'], 'real_negative_prompt': task['log_negative_prompt'],
-        #     # prompt with resolved wildcards, styles and prompt expansion
-        #     'complete_prompt_positive': task['positive'], 'complete_prompt_negative': task['negative'],
-        #     'styles': str(raw_style_selections),
-        #     'seed': task['task_seed'], 'width': width, 'height': height,
-        #     'sampler': sampler_name, 'scheduler': scheduler_name, 'performance': performance_selection,
-        #     'steps': steps, 'refiner_switch': refiner_switch, 'sharpness': sharpness, 'cfg': cfg_scale,
-        #     'base_model': base_model_name, 'base_model_hash': base_model_hash, 'refiner_model': refiner_model_name,
-        #     'denoising_strength': denoising_strength,
-        #     'freeu': advanced_parameters.freeu_enabled,
-        #     'img2img': input_image_checkbox,
-        #     'prompt_expansion': task['expansion']
-        # }
-        #
-        # if advanced_parameters.freeu_enabled:
-        #     metadata |= {
-        #         'freeu_b1': advanced_parameters.freeu_b1, 'freeu_b2': advanced_parameters.freeu_b2,
-        #         'freeu_s1': advanced_parameters.freeu_s1, 'freeu_s2': advanced_parameters.freeu_s2
-        #     }
-        #
-        # if 'vary' in goals:
-        #     metadata |= {
-        #         'uov_method': uov_method
-        #     }
-        #
-        # if 'upscale' in goals:
-        #     metadata |= {
-        #         'uov_method': uov_method, 'scale': f
-        #     }
-        #
-        # if 'inpaint' in goals:
-        #     if len(outpaint_selections) > 0:
-        #         metadata |= {
-        #             'outpaint_selections': outpaint_selections
-        #         }
-        #
-        #     metadata |= {
-        #         'inpaint_additional_prompt': inpaint_additional_prompt,
-        #         'inpaint_mask_upload': advanced_parameters.inpaint_mask_upload_checkbox,
-        #         'invert_mask': advanced_parameters.invert_mask_checkbox,
-        #         'inpaint_disable_initial_latent': advanced_parameters.inpaint_disable_initial_latent,
-        #         'inpaint_engine': advanced_parameters.inpaint_engine,
-        #         'inpaint_strength': advanced_parameters.inpaint_strength,
-        #         'inpaint_respective_field': advanced_parameters.inpaint_respective_field,
-        #     }
-        #
-        # if 'cn' in goals:
-        #     metadata |= {
-        #         'canny_low_threshold': advanced_parameters.canny_low_threshold,
-        #         'canny_high_threshold': advanced_parameters.canny_high_threshold,
-        #     }
-        #
-        #     ip_list = {x: [] for x in flags.ip_list}
-        #     cn_task_index = 1
-        #     for cn_type in ip_list:
-        #         for cn_task in cn_tasks[cn_type]:
-        #             cn_img, cn_stop, cn_weight = cn_task
-        #             metadata |= {
-        #                 f'image_prompt_{cn_task_index}': {
-        #                     'cn_type': cn_type, 'cn_stop': cn_stop, 'cn_weight': cn_weight,
-        #                 }
-        #             }
-        #             cn_task_index += 1
-        #
-        # metadata |= {
-        #     'software': f'Fooocus v{fooocus_version.version}',
-        # }
-        # TODO add metadata_created_by
-        # if modules.config.metadata_created_by != '':
-        #     metadata |= {
-        #         'created_by': modules.config.metadata_created_by
-        #     }
-        # # return json.dumps(metadata, ensure_ascii=True) TODO check if possible
-        # return json.dumps(metadata, ensure_ascii=False)
 
     @staticmethod
     def replace_value_with_filename(key, value, filenames):
@@ -319,12 +238,6 @@ def get_metadata_parser(metadata_scheme: MetadataScheme) -> MetadataParser:
         case _:
             raise NotImplementedError
 
-# IGNORED_INFO_KEYS = {
-#     'jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif',
-#     'loop', 'background', 'timestamp', 'duration', 'progressive', 'progression',
-#     'icc_profile', 'chromaticity', 'photoshop',
-# }
-
 
 def read_info_from_image(filepath) -> tuple[str | None, dict, MetadataScheme | None]:
     with Image.open(filepath) as image:
@@ -346,37 +259,4 @@ def read_info_from_image(filepath) -> tuple[str | None, dict, MetadataScheme | N
     if metadata_scheme is None and isinstance(parameters, str):
         metadata_scheme = modules.metadata.MetadataScheme.A1111
 
-    # TODO code cleanup
-    # if "exif" in items:
-    #     exif_data = items["exif"]
-    #     try:
-    #         exif = piexif.load(exif_data)
-    #     except OSError:
-    #         # memory / exif was not valid so piexif tried to read from a file
-    #         exif = None
-    #     exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')
-    #     try:
-    #         exif_comment = piexif.helper.UserComment.load(exif_comment)
-    #     except ValueError:
-    #         exif_comment = exif_comment.decode('utf8', errors="ignore")
-    #
-    #     if exif_comment:
-    #         items['exif comment'] = exif_comment
-    #         parameters = exif_comment
-
-    # for field in IGNORED_INFO_KEYS:
-    #     items.pop(field, None)
-
-    #     if items.get("Software", None) == "NovelAI":
-    #         try:
-    #             json_info = json.loads(items["Comment"])
-    #             sampler = sd_samplers.samplers_map.get(json_info["sampler"], "Euler a")
-    #
-    #             geninfo = f"""{items["Description"]}
-    # Negative prompt: {json_info["uc"]}
-    # Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Clip skip: 2, ENSD: 31337"""
-    #         except Exception:
-    #             errors.report("Error parsing NovelAI image generation parameters",
-    #                           exc_info=True)
-
     return parameters, items, metadata_scheme