HivisionIDPhoto旨在开发一种实用的证件照智能制作算法。
它利用一套完善的模型工作流程，实现对多种用户拍照场景的识别、抠图与证件照生成。
HivisionIDPhoto可以做到:
- 轻量级抠图
- 根据不同尺寸规格生成不同的标准证件照、六寸排版照
- 美颜（waiting）
- 智能换正装（waiting）
如果HivisionIDPhoto对你有帮助，请star这个repo或推荐给你的朋友，解决证件照应急制作问题！
使用建议更新到最新的 gradio
|
1 2 3 4 5 6 7 8 |
conda create -yn HivisionIDPhotos python=3.10 conda activate HivisionIDPhotos pip install -r requirements.txt pip install -U gradio python app.py |
里面的代码 gradio 可能需要修改，修改后的 app.py 代码
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 |
import gradio as gr import onnxruntime from src.face_judgement_align import IDphotos_create from hivisionai.hycv.vision import add_background from src.layoutCreate import generate_layout_photo, generate_layout_image import pathlib import numpy as np size_list_dict = {"一寸": (413, 295), "二寸": (626, 413), "教师资格证": (413, 295), "国家公务员考试": (413, 295), "初级会计考试": (413, 295)} color_list_dict = {"蓝色": (86, 140, 212), "白色": (255, 255, 255), "红色": (233, 51, 35)} # 设置Gradio examples def set_example_image(example: list) -> dict: #return gr.Image.update(value=example[0]) return example[0] # 检测RGB是否超出范围，如果超出则约束到0～255之间 def range_check(value, min_value=0, max_value=255): value = int(value) if value <= min_value: value = min_value elif value > max_value: value = max_value return value def idphoto_inference(input_image, mode_option, size_list_option, color_option, render_option, custom_color_R, custom_color_G, custom_color_B, custom_size_height, custom_size_width, head_measure_ratio=0.2, head_height_ratio=0.45, top_distance_max=0.12, top_distance_min=0.10): idphoto_json = { "size_mode": mode_option, "color_mode": color_option, "render_mode": render_option, } # 如果尺寸模式选择的是尺寸列表 if idphoto_json["size_mode"] == "尺寸列表": idphoto_json["size"] = size_list_dict[size_list_option] # 如果尺寸模式选择的是自定义尺寸 elif idphoto_json["size_mode"] == "自定义尺寸": id_height = int(custom_size_height) id_width = int(custom_size_width) if id_height < id_width or min(id_height, id_width) < 100 or max(id_height, id_width) > 1800: return { img_output_standard: gr.update(value=None), img_output_standard_hd: gr.update(value=None), notification: gr.update(value="宽度应不大于长度；长宽不应小于100，大于1800", visible=True)} idphoto_json["size"] = (id_height, id_width) else: idphoto_json["size"] = (None, None) # 如果颜色模式选择的是自定义底色 if idphoto_json["color_mode"] == "自定义底色": idphoto_json["color_bgr"] = (range_check(custom_color_R), range_check(custom_color_G), range_check(custom_color_B)) else: idphoto_json["color_bgr"] = color_list_dict[color_option] result_image_hd, result_image_standard, typography_arr, typography_rotate, \ _, _, _, _, status = IDphotos_create(input_image, mode=idphoto_json["size_mode"], size=idphoto_json["size"], head_measure_ratio=head_measure_ratio, head_height_ratio=head_height_ratio, align=False, beauty=False, fd68=None, human_sess=sess, IS_DEBUG=False, top_distance_max=top_distance_max, top_distance_min=top_distance_min) # 如果检测到人脸数量不等于1 if status == 0: result_messgae = { img_output_standard: gr.update(value=None), img_output_standard_hd: gr.update(value=None), notification: gr.update(value="人脸数量不等于1", visible=True) } # 如果检测到人脸数量等于1 else: if idphoto_json["render_mode"] == "纯色": result_image_standard = np.uint8( add_background(result_image_standard, bgr=idphoto_json["color_bgr"])) result_image_hd = np.uint8(add_background(result_image_hd, bgr=idphoto_json["color_bgr"])) elif idphoto_json["render_mode"] == "上下渐变(白)": result_image_standard = np.uint8( add_background(result_image_standard, bgr=idphoto_json["color_bgr"], mode="updown_gradient")) result_image_hd = np.uint8( add_background(result_image_hd, bgr=idphoto_json["color_bgr"], mode="updown_gradient")) else: result_image_standard = np.uint8( add_background(result_image_standard, bgr=idphoto_json["color_bgr"], mode="center_gradient")) result_image_hd = np.uint8( add_background(result_image_hd, bgr=idphoto_json["color_bgr"], mode="center_gradient")) if idphoto_json["size_mode"] == "只换底": result_layout_image = gr.update(visible=False) else: typography_arr, typography_rotate = generate_layout_photo(input_height=idphoto_json["size"][0], input_width=idphoto_json["size"][1]) result_layout_image = generate_layout_image(result_image_standard, typography_arr, typography_rotate, height=idphoto_json["size"][0], width=idphoto_json["size"][1]) result_messgae = { img_output_standard: result_image_standard, img_output_standard_hd: result_image_hd, img_output_layout: result_layout_image, notification: gr.update(visible=False)} return result_messgae if __name__ == "__main__": HY_HUMAN_MATTING_WEIGHTS_PATH = "./hivision_modnet.onnx" sess = onnxruntime.InferenceSession(HY_HUMAN_MATTING_WEIGHTS_PATH) size_mode = ["尺寸列表", "只换底", "自定义尺寸"] size_list = ["一寸", "二寸", "教师资格证", "国家公务员考试", "初级会计考试"] colors = ["蓝色", "白色", "红色", "自定义底色"] render = ["纯色", "上下渐变(白)", "中心渐变(白)"] title = "<h1 id='title'>HivisionIDPhotos</h1>" description = "<h3>😎6.20更新：新增尺寸选择列表</h3>" css = ''' h1#title, h3 { text-align: center; } ''' demo = gr.Blocks(css=css) with demo: gr.Markdown(title) gr.Markdown(description) with gr.Row(): with gr.Column(): #img_input = gr.Image().style(height=350) img_input = gr.Image(height=350) mode_options = gr.Radio(choices=size_mode, label="证件照尺寸选项", value="尺寸列表", elem_id="size") # 预设尺寸下拉菜单 with gr.Row(visible=True) as size_list_row: size_list_options = gr.Dropdown(choices=size_list, label="预设尺寸", value="一寸", elem_id="size_list") with gr.Row(visible=False) as custom_size: custom_size_height = gr.Number(value=413, label="height", interactive=True) custom_size_wdith = gr.Number(value=295, label="width", interactive=True) color_options = gr.Radio(choices=colors, label="背景色", value="蓝色", elem_id="color") with gr.Row(visible=False) as custom_color: custom_color_R = gr.Number(value=0, label="R", interactive=True) custom_color_G = gr.Number(value=0, label="G", interactive=True) custom_color_B = gr.Number(value=0, label="B", interactive=True) render_options = gr.Radio(choices=render, label="渲染方式", value="纯色", elem_id="render") img_but = gr.Button('开始制作') # 案例图片 example_images = gr.Dataset(components=[img_input], samples=[[path.as_posix()] for path in sorted(pathlib.Path('images').rglob('*.jpg'))]) with gr.Column(): notification = gr.Text(label="状态", visible=False) with gr.Row(): #img_output_standard = gr.Image(label="标准照").style(height=350) #img_output_standard_hd = gr.Image(label="高清照").style(height=350) img_output_standard = gr.Image(label="标准照", height=350) img_output_standard_hd = gr.Image(label="高清照", height=350) #img_output_layout = gr.Image(label="六寸排版照").style(height=350) img_output_layout = gr.Image(label="六寸排版照", height=350) def change_color(colors): if colors == "自定义底色": return {custom_color: gr.update(visible=True)} else: return {custom_color: gr.update(visible=False)} def change_size_mode(size_option_item): if size_option_item == "自定义尺寸": return {custom_size: gr.update(visible=True), size_list_row: gr.update(visible=False)} elif size_option_item == "只换底": return {custom_size: gr.update(visible=False), size_list_row: gr.update(visible=False)} else: return {custom_size: gr.update(visible=False), size_list_row: gr.update(visible=True)} color_options.input(change_color, inputs=[color_options], outputs=[custom_color]) mode_options.input(change_size_mode, inputs=[mode_options], outputs=[custom_size, size_list_row]) img_but.click(idphoto_inference, inputs=[img_input, mode_options, size_list_options, color_options, render_options, custom_color_R, custom_color_G, custom_color_B, custom_size_height, custom_size_wdith], outputs=[img_output_standard, img_output_standard_hd, img_output_layout, notification], queue=True) example_images.click(fn=set_example_image, inputs=[example_images], outputs=[img_input]) #demo.launch(enable_queue=True) demo.launch() |