12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273 |
- # Copyright (c) Alibaba, Inc. and its affiliates.
- import os
- import json
- from facechain.inference_fact import GenPortrait
- import cv2
- from facechain.utils import snapshot_download
- from facechain.constants import neg_prompt, pos_prompt_with_cloth, pos_prompt_with_style, base_models
- def generate_pos_prompt(style_model, prompt_cloth):
- if style_model is not None:
- matched = list(filter(lambda style: style_model == style['name'], styles))
- if len(matched) == 0:
- raise ValueError(f'styles not found: {style_model}')
- matched = matched[0]
- if matched['model_id'] is None:
- pos_prompt = pos_prompt_with_cloth.format(prompt_cloth)
- else:
- pos_prompt = pos_prompt_with_style.format(matched['add_prompt_style'])
- else:
- pos_prompt = pos_prompt_with_cloth.format(prompt_cloth)
- return pos_prompt
- styles = []
- for base_model in base_models:
- style_in_base = []
- folder_path = f"styles/{base_model['name']}"
- files = os.listdir(folder_path)
- files.sort()
- for file in files:
- file_path = os.path.join(folder_path, file)
- with open(file_path, "r") as f:
- data = json.load(f)
- style_in_base.append(data['name'])
- styles.append(data)
- base_model['style_list'] = style_in_base
- use_pose_model = False
- input_img_path = 'poses/man/pose2.png'
- pose_image = 'poses/man/pose1.png'
- num_generate = 5
- multiplier_style = 0.25
- output_dir = './generated'
- base_model_idx = 0
- style_idx = 0
- base_model = base_models[base_model_idx]
- style = styles[style_idx]
- model_id = style['model_id']
- if model_id == None:
- style_model_path = None
- pos_prompt = generate_pos_prompt(style['name'], style['add_prompt_style'])
- else:
- if os.path.exists(model_id):
- model_dir = model_id
- else:
- model_dir = snapshot_download(model_id, revision=style['revision'])
- style_model_path = os.path.join(model_dir, style['bin_file'])
- pos_prompt = generate_pos_prompt(style['name'], style['add_prompt_style']) # style has its own prompt
- if not use_pose_model:
- pose_image = None
- gen_portrait = GenPortrait()
- outputs = gen_portrait(num_generate, base_model_idx, style_model_path, pos_prompt, neg_prompt, input_img_path, pose_image, multiplier_style)
- os.makedirs(output_dir, exist_ok=True)
- for i, out_tmp in enumerate(outputs):
- cv2.imwrite(os.path.join(output_dir, f'{i}.png'), out_tmp)
|