Update space

app.py

@@ -1,154 +1,174 @@
 import gradio as gr
-import numpy as np
-import random
+from sugg_gene import suggest_gene
+from clothGen import cloth_gen
+from user_dress import user_cloths
+import requests
+import os
+from io import BytesIO
+from PIL import Image
+from cal_compatibility import cal_compatibility
 
-# import spaces #[uncomment to use ZeroGPU]
-from diffusers import DiffusionPipeline
-import torch
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
+gen_pic_num = 6
+save_directory = "downloads"
 
-if torch.cuda.is_available():
-    torch_dtype = torch.float16
-else:
-    torch_dtype = torch.float32
 
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
+def get_select_index(evt: gr.SelectData, gallery):
+    print(gallery[evt.index][0])
+    with open(os.path.join(save_directory, f"cloth_intro_{evt.index+1}.txt"), "r") as f:
+        introduction = f.read()
+    return gallery[evt.index][0], introduction
 
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
 
+def update_choices(dropout1, dropout2,):
+    if dropout1 == "男":
+        option = ['倒三角形', '矩形', '苹果形', '沙漏型', '胖型']
+    else:
+        option = ["梨形", "草莓形", "沙漏形", "标准", "苹果形"]
+    dropout2 = gr.Dropdown(choices=option)
+    return dropout2
 
-# @spaces.GPU #[uncomment to use ZeroGPU]
-def infer(
-    prompt,
-    negative_prompt,
-    seed,
-    randomize_seed,
-    width,
-    height,
-    guidance_scale,
-    num_inference_steps,
-    progress=gr.Progress(track_tqdm=True),
-):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-
-    generator = torch.Generator().manual_seed(seed)
-
-    image = pipe(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        width=width,
-        height=height,
-        generator=generator,
-    ).images[0]
-
-    return image, seed
-
-
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
-
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 640px;
-}
-"""
-
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
-
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-
-            run_button = gr.Button("Run", scale=0, variant="primary")
-
-        result = gr.Image(label="Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-                visible=False,
-            )
-
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
 
+with gr.Blocks(theme=gr.themes.Base()) as demo:
+    with gr.Row():
+        # 左侧模块
+        with gr.Column(scale=1):
             with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
+                gr.Markdown(""
+                            "# 用户信息"
+                            "")
             with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
-                )
+                text_input1 = gr.Textbox(label="用户姓名", min_width=100)
+                text_input2 = gr.Textbox(label="身高/cm", min_width=100)
+                text_input3 = gr.Textbox(label="体重/kg", min_width=100)
+                text_input4 = gr.Textbox(label="腰围/cm", min_width=100)
+                text_input5 = gr.Textbox(label="胸围/cm", min_width=100)
+                text_input6 = gr.Textbox(label="臀围/cm", min_width=100)
+                text_input7 = gr.Textbox(label="肩���/cm", min_width=100)
+                text_input8 = gr.Textbox(label="腿长/cm", min_width=100)
+                text_input9 = gr.Textbox(label="臂长/cm", min_width=100)
+                dropdown_options1 = ["女", "男"]
+                dropdown_input1 = gr.Dropdown(choices=dropdown_options1, label="性别", min_width=100)
+                dropdown_input2 = gr.Dropdown(choices=["梨形", "草莓形", "沙漏形", "标准", "苹果形"], label="体型分类", min_width=100)
+                dropdown_input1.change(fn=update_choices, inputs=[dropdown_input1, dropdown_input2], outputs=dropdown_input2)
+                dropdown_options3 = ["浅色", "中等偏黄色", "中等偏褐色", "深色"]
+                dropdown_input3 = gr.Dropdown(choices=dropdown_options3, label="肤色", min_width=100)
+                text_input10 = gr.Textbox(label="穿衣风格偏好", min_width=1000)
+                text_input11 = gr.Textbox(label="生话方式和场景需求", min_width=1000)
+                text_input12 = gr.Textbox(label="其他特殊需求", min_width=1000)
+            with gr.Row():
+                user_pic = gr.Image(label="用户照片", value="model.jpg", height=550, width=300)
 
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=2,  # Replace with defaults that work for your model
+        # 右侧模块
+        with gr.Column(scale=2):
+            with gr.Row():
+                gr.Markdown(""
+                            "# 穿搭建议"
+                            "")
+            with gr.Row():
+                text_output1 = gr.Textbox(label="穿搭建议", lines=12, max_lines=12, interactive=False, show_label=False,
+                                          min_width=1000)
+                submit_button_1 = gr.Button("AI智能分析，生成穿搭建议", min_width=1000)
+            image_output_1 = gr.Image(label="显示图像", value="image 209.png")
+
+            gallery_1 = gr.Gallery(
+                label="服装", elem_id="gallery", interactive=False,
+                value=[
+                    # os.path.join(example_path, '上衣/_WEB_2016_09_26__2016092617451357e8ee2957aa1_TD.jpg'),
+                    # os.path.join(example_path, '上衣/_WEB_2016_09_27__2016092717211057ea3a069c749_TD.jpg'),
+                    # os.path.join(example_path, '上衣/_WEB_2016_09_27__2016092717391657ea3e446ce3f_TD.jpg'),
+                    # os.path.join(example_path, '上衣/_WEB_2016_09_27__2016092717573057ea428a305bc_TD.jpg'),
+                    # os.path.join(example_path, '上衣/_WEB_2016_09_28__2016092810150157eb27a56a631_TD.jpg'),
+                    # os.path.join(example_path, '上衣/_WEB_2016_09_28__2016092810464557eb2f15e1df3_TD.jpg'),
+                ],
+                columns=[4], rows=[2], object_fit="contain", height=250, min_width=450)
+
+            gallery_3 = gr.Gallery(
+                label="配饰", elem_id="gallery",
+                value=[
+                    'downloads/access_1.jpg',
+                    'downloads/access_2.jpg',
+                    'downloads/access_3.jpg',
+                    'downloads/access_4.jpg',
+                    'downloads/access_5.jpg',
+                    'downloads/access_6.jpg',
+                    'downloads/access_7.jpg',
+                    'downloads/access_8.jpg',
+                ],
+                columns=[4], rows=[2], object_fit="contain", height=250, min_width=450)
+            submit_button_2 = gr.Button("AI智能分析，生成民族服饰")
+
+        with gr.Column(scale=2):
+            with gr.Row():
+                gr.Markdown(""
+                            "# 搭配生成"
+                            "")
+            with gr.Row():
+                gallery_4 = gr.Gallery(
+                    label="套装", elem_id="gallery",
+                    value=[],
+                    columns=[3], rows=[1], object_fit="contain", height=180, min_width=450)
+            with gr.Row():
+                submit_button_3 = gr.Button("服饰及搭配兼容性排序")
+            with gr.Row():
+                image_output_5 = gr.Image(label="显示图像", show_label=False, min_width=200, height=350, interactive=False)
+                intro = gr.Textbox(label="服饰介绍", lines=14, max_lines=14)
+            with gr.Row():
+                gallery_user = gr.Gallery(
+                    label="试穿结果",
+                    elem_id="gallery",
+                    value=[],
+                    columns=[3], rows=[2],
+                    object_fit="contain",
+                    min_width=200,
+                    height=350,
                 )
-
-        gr.Examples(examples=examples, inputs=[prompt])
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
-        inputs=[
-            prompt,
-            negative_prompt,
-            seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
-        ],
-        outputs=[result, seed],
-    )
-
-if __name__ == "__main__":
-    demo.launch()
+            with gr.Row():
+                submit_button_4 = gr.Button("虚拟试穿")
+            with gr.Row():
+                feedback = gr.Textbox(label="反馈", placeholder="可以从款式、颜色、图案、风格倾向、文化偏好角度进行反馈", lines=1,
+                                      max_lines=1, elem_id="feedback")
+            with gr.Row():
+                submit_button_5 = gr.Button("反馈")
+    with gr.Row():
+        gr.Markdown("""
+                    女性体型备注：
+                    1. **梨形身材**：臀围比胸围**至少大5.08厘米**
+                    2. **草莓形身材**：臀围比胸围**至少小5.08厘米**
+                    3. **沙漏形身材**：胸围比腰围**至少大3.81厘米**且腰部线条明显
+                    4. **标准身材**：胸围比腰围**至少大3.81厘米**且腰部线条不明显
+                    5. **苹果形身材**：胸围比腰围**至少小3.81厘米**
+                    
+                    男性体型备注：
+                    1. **倒三角形身材**：肩宽比腰围**至少大10厘米**  
+                    2. **矩形身材**：肩宽与腰围的差异**小于5厘米**  
+                    3. **苹果形身材**：腰围比肩宽**至少大7.5厘米**  
+                    4. **沙漏型身材**：腰围比肩宽或臀围**至少小10厘米**，且肩宽和臀围的差异**小于5厘米**  
+                    5. **胖型身材**：腰围比胸围或肩宽**至少大10厘米**
+                    """)
+
+    submit_button_1.click(fn=suggest_gene,
+                          inputs=[text_input1, text_input2, text_input3, text_input4, text_input5,
+                                  text_input6, text_input7, text_input8, text_input9, dropdown_input1,
+                                  dropdown_input2, dropdown_input3, text_input10, text_input11, text_input12,
+                                  feedback, user_pic],
+                          outputs=[text_output1])
+    submit_button_2.click(fn=cloth_gen,
+                          inputs=dropdown_input1,
+                          outputs=[gallery_1, image_output_5, intro])
+
+    gallery_1.select(fn=get_select_index, inputs=gallery_1, outputs=[image_output_5, intro])
+    submit_button_3.click(fn=cal_compatibility,
+                          inputs=[],
+                          outputs=[gallery_4])
+    submit_button_4.click(fn=user_cloths,
+                          inputs=[user_pic, image_output_5],
+                          outputs=gallery_user)
+    submit_button_5.click(fn=suggest_gene,
+                          inputs=[text_input1, text_input2, text_input3, text_input4, text_input5,
+                                  text_input6, text_input7, text_input8, text_input9, dropdown_input1,
+                                  dropdown_input2, dropdown_input3, text_input10, text_input11, text_input12,
+                                  feedback, user_pic],
+                          outputs=[text_output1])
+
+demo.launch(server_port=7860, share=True)