Upload 2024002452.py

2024002452.py

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+import gradio as gr
+import paddle
+import requests
+import json
+from ppdiffusers import StableDiffusionInpaintPipeline
+from ppdiffusers import StableDiffusionImg2ImgPipeline
+from ppdiffusers import PaintByExamplePipeline
+from ppdiffusers.utils import load_image
+
+pipe = None  #全局变量，用于模型的导入
+API_KEY = "j5HodGgjG2iQ87MenXrw2hot"
+SECRET_KEY = "Ea1AYc1kjzv2MNExEZeMAEwzanDDlsdK"
+def select_model(choice):#用于选择模型
+    global pipe
+    pipe = None
+    paddle.device.cuda.empty_cache() #释放GPU显存
+    if choice == '文本引导图片风格变化':
+        pipe1 = StableDiffusionImg2ImgPipeline.from_pretrained("/home/aistudio/model1")
+    elif choice == '文本引导图像区域生成':
+        pipe1 = StableDiffusionInpaintPipeline.from_pretrained("/home/aistudio/model2")
+    elif choice == '文图引导图像区域生成':
+        pipe1 = PaintByExamplePipeline.from_pretrained("/home/aistudio/model3")
+    pipe = pipe1
+    return pipe1  #用于输出导入的模型相关信息
+
+def get_access_token():
+    """
+    使用 AK，SK 生成鉴权签名（Access Token）
+    :return: access_token，或是None(如果错误)
+    """
+    url = "https://aip.baidubce.com/oauth/2.0/token"
+    params = {"grant_type": "client_credentials", "client_id": API_KEY, "client_secret": SECRET_KEY}
+    return str(requests.post(url, params=params).json().get("access_token"))
+
+def translation(content):  #可接受中文prompt 转换成英文
+    url = "https://aip.baidubce.com/rpc/2.0/mt/texttrans/v1?access_token=" + get_access_token()
+    payload = json.dumps({
+        "from": "zh",
+        "to": "en",
+        "q": content
+    })
+    headers = {
+        'Content-Type': 'application/json',
+        'Accept': 'application/json'
+    }
+    response = requests.request("POST", url, headers=headers, data=payload)
+    i = response.text.find("dst")+6
+    j = response.text.find("src")-2
+    return response.text[i:j]
+
+
+def diffusion_image(image,text,strength,guidance_scale,choice):
+    global pipe
+    text = translation(text)
+    if choice == '文本引导图片风格变化':
+        image = load_image(image).resize((768, 512))
+        with paddle.amp.auto_cast(True): # 使用fp16加快生成速度
+            img = pipe(prompt=text, image=image, strength=strength, guidance_scale=guidance_scale).images[0]
+    elif choice == '文本引导图像区域生成':
+        init_image = load_image(image).resize((512, 512))
+        mask_image = load_image(strength).resize((512, 512))
+        with paddle.amp.auto_cast(True): # 使用fp16加快生成速度
+            img = pipe(prompt=text, image=init_image, mask_image=mask_image).images[0]
+    elif choice == '文图引导图像区域生成':
+        init_image = load_image(image).resize((512, 512))
+        mask_image = load_image(strength).resize((512, 512))
+        example_image = load_image(guidance_scale).resize((512, 512))
+        with paddle.amp.auto_cast(True): # 使用fp16加快生成速度
+            img = pipe(image=init_image, mask_image=mask_image, example_image=example_image).images[0]
+    return img
+
+options = ["文本引导图片风格变化", "文本引导图像区域生成", "文图引导图像区域生成",'文图双引导生成'] # 定义下拉选项
+
+def select_option(choice):
+    return select_model(choice)
+
+
+with gr.Blocks(title='功能选择') as demo:
+    gr.Markdown("# 功能介绍")
+    gr.Markdown("根据提示输入，得到理想图像！")
+    with gr.Row():
+        pipeText = gr.Textbox(label ='模型信息')
+        with gr.Tab('加载模型'):
+            dropdown = gr.inputs.Dropdown(choices=options, label="选项") # 创建下拉选择框输入组件
+            sub_model = gr.Button("加载模型")
+            with gr.Row():
+                with gr.Tab('文本引导图片风格变化'):
+                    in_img_1 = gr.Image(label='输入图片',type="filepath")
+                    text_1 = gr.Textbox(label="输入文字")
+                    strength_1 = gr.Slider(label="强度", minimum=0, maximum=1, step=0.01,value=0.75,
+                                    info="控制条件或指导文本的强度")
+                    guidance_scale_1 = gr.Slider(label="权重", minimum=0, maximum=15, step=0.1,value=7.5,
+                                    info="条件或指导的权重")
+                    sub_img_1 = gr.Button("生成图片")
+                with gr.Tab('文本引导图像区域生成'):
+                    in_img_2 = gr.Image(label='输入图片',type="filepath")
+                    strength_2 = gr.Image(label='输入掩码',type="filepath")
+                    text_2 = gr.Textbox(label="输入文字")
+                    sub_img_2 = gr.Button("生成图片")
+                with gr.Tab('文图引导图像区域生成'):
+                    in_img_3 = gr.Image(label='输入图片',type="filepath")
+                    strength_3 = gr.Image(label='输入掩码',type="filepath")
+                    guidance_scale_3 = gr.Image(label='��入目标图片',type="filepath")
+                    sub_img_3 = gr.Button("生成图片")
+    out_img=gr.Image(label='输出图片')
+    sub_model.click(fn =select_option,inputs=dropdown,outputs=pipeText)
+    sub_img_1.click(fn=diffusion_image, inputs=[in_img_1,text_1,strength_1,guidance_scale_1,dropdown], outputs=out_img)
+    sub_img_2.click(fn=diffusion_image, inputs=[in_img_2,text_2,strength_2,guidance_scale_1,dropdown], outputs=out_img)
+demo.launch()