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run_inference.py
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run_inference.py
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# 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)