xsl
443cfa298f
包含： - hair_service_sd: 主服务（换发型/换发色/生发，端口8801） - photo_service: LoRA调度+训练（端口32678） - hair_grow_service: 调试测试页（端口8888，含4个测试页） - 批量训练脚本（batch_train_hairstyles.py） - 发际线mask自动识别（hairline_mask.py，4种方案） - 手绘mask换发型（hair_swap_manual.py） - 文档：README.md + LARGE_FILES.md + docs/ 大文件（模型权重200G、训练数据123G）已排除，见 LARGE_FILES.md OSS/COS密钥已脱敏为环境变量，原文件备份在本地
103 lines
3.9 KiB
Python
103 lines
3.9 KiB
Python
import gradio as gr
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import os,re
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import numpy as np
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import requests
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import cv2
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import base64
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import json
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from io import BytesIO
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from PIL import Image
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# api_service_url = 'http://127.0.0.1:1234'
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# api_service_url = 'http://i-2.gpushare.com:53412'
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api_service_url = 'http://service.aicloud.fit:7393/api/hairStyle/v1'
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class ChangeHairGui():
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# def __init__(self):
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# a = 1
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def change_hair(self, user_img, hair_img):
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if user_img is None or user_img is None:
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return None
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#
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# if user_img.shape != hair_img.shape:
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# hair_img = cv2.resize(hair_img, (user_img.shape[1], user_img.shape[0]))
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#
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# alpha = 0.5 # 图像1的权重
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# beta = 0.5 # 图像2的权重
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# gamma = 0 # 亮度调整常量（通常为0）
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#
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# result_image = cv2.addWeighted(user_img, alpha, hair_img, beta, gamma)
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# 将 Pillow 图像转换为 OpenCV 格式（BGR）
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user_img = cv2.cvtColor(np.array(user_img), cv2.COLOR_RGB2BGR)
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hair_img = cv2.cvtColor(np.array(hair_img), cv2.COLOR_RGB2BGR)
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# 将模板图片转换为base64格式
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retval, user_bytes = cv2.imencode('.jpg', user_img)
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encoded_user_image = base64.b64encode(user_bytes).decode('utf-8')
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retval, hair_bytes = cv2.imencode('.jpg', hair_img)
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encoded_hair_image = base64.b64encode(hair_bytes).decode('utf-8')
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url = api_service_url
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# 请求换发型接口
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payload = json.dumps({
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"user_img_base64": encoded_user_image,
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"hair_ref_img_base64": encoded_hair_image
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})
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headers = {
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'Content-Type': 'application/json'
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}
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print('请求api_service.py发送请求！！')
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response = requests.request("POST", url, headers=headers, data=payload)
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print('请求api_service.py发送请求成功！！')
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if response.status_code != 200:
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raise RuntimeError(f"Failed to send request to API service. Status code: {response.status_code}")
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ret_image_b64 = response.json().get('result')
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if ret_image_b64 is None:
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raise RuntimeError(f"ret image failed!")
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image_array = np.frombuffer(base64.b64decode(ret_image_b64), np.uint8)
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result_image = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
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result_image = cv2.cvtColor(result_image, cv2.COLOR_BGR2RGB)
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dst_size = max(result_image.shape[0], result_image.shape[1])
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M = cv2.getRotationMatrix2D((result_image.shape[1] / 2, result_image.shape[0] / 2), 0, 1)
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M[:, 2] += np.float32([dst_size / 2 - result_image.shape[1] / 2, dst_size / 2 - result_image.shape[0] / 2])
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result_image = cv2.warpAffine(result_image, M, (dst_size, dst_size), borderValue=(255, 255, 255))
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return result_image
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def start_gui(self):
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with gr.Blocks() as demo:
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with gr.Row():
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gr.Markdown("# 数字力场换发型效果展示")
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# 换脸
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with gr.Tab("换发型"):
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with gr.Row():
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gr.Markdown("#换发型")
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with gr.Row():
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with gr.Column():
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user_img = gr.Image(label="请上传用户图片", type="numpy", height=384, width=384)
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with gr.Column():
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hair_img = gr.Image(label="请上传发型图片", type="numpy", height=384, width=384)
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with gr.Column():
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output_img = gr.Image(label="结果展示", type="numpy", height=384, width=384, format='png')
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with gr.Column():
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run_button = gr.Button(value="提交")
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run_button.click(self.change_hair, inputs=[user_img, hair_img], outputs=[output_img])
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demo.launch(server_name='0.0.0.0', server_port=8080)
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if __name__ == '__main__':
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demo = ChangeHairGui()
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demo.start_gui()
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