try

app.py

@@ -0,0 +1,88 @@
+import gradio as gr
+import os
+from PIL import Image
+
+root = "/mnt/ve_share/generation/data/result/diffusions/vis/instructpix2pix/official"
+log_path = "/mnt/ve_share/generation/recordx.txt"
+
+def feedback(feedback_text, model, scene):
+    output = "%s@%s@%s@%s" % (model, scene, feedback_text, length)
+    with open(log_path, "a") as input_file:
+        input_file.writelines(output + "\n")
+        print(output)
+   
+def get_file_paths(folder_path):
+    file_paths = []
+    for root, dirs, files in os.walk(folder_path):
+        for file in files:
+            file_path = os.path.join(root, file)
+            file_paths.append(file_path)
+    return file_paths 
+
+def generation_eval():
+    # print("request.headers: ", request.headers)
+    models = [f for f in os.listdir(root) if os.path.isdir(os.path.join(root, f))]
+    model_root = "%s/%s" % (root, models[-2])
+    scenes = [f for f in os.listdir(model_root) if os.path.isdir(os.path.join(model_root, f))]
+
+    def clip_api(model, scene):
+        # global feedback_btn
+        # feedback_btn = gr.Radio.update(choices=['未知(反馈可持续优化LSU🤗)', '准确率低(<30%)', '准确率中(30% ~ 80%)', '准确率高(>80%)',], value='未知(反馈可持续优化LSU🤗)')
+        ret_imgs = get_file_paths("%s/%s/%s" % (root, model, scene))
+        # print(ret_imgs)
+        global length
+        length = len(ret_imgs)
+        ret_imgs = [Image.open(_) for _ in ret_imgs]
+        return ret_imgs
+
+    examples = []
+    # examples = [
+    #     ["道路上工作的环卫工人", 20, VLP, "是"],
+    #     ["雨天打伞的人", 20, VLP, "是"],
+    #     ["救护车", 20, VLP, "是"],
+    #     ["校车", 20, VLP, "是"],
+    #     ["警车", 20, VLP, "是"],
+    #     ["喝水的人", 20, VLP, "是"],
+    #     ["后备箱打开", 20, VLP, "是"],
+    # ]
+
+    title = "<h1 align='center'>图像生成人工评测平台</h1>"
+
+    with gr.Blocks() as demo:
+        gr.Markdown(title)
+        # gr.Markdown(description)
+        with gr.Row():
+            with gr.Column(scale=1):
+                # with gr.Column(scale=2):
+                #     text = gr.Textbox(value="道路上工作的环卫工人", label="请填写文本", elem_id=0, interactive=True)
+
+                # num = gr.components.Slider(minimum=0, maximum=200, step=1, value=30, label="返回图片数", elem_id=2)
+                model = gr.components.Radio(label="模型选择", choices=models, value=models[0], elem_id=3)
+                scene = gr.components.Radio(label="场景选择", choices=scenes, value=scenes[0], elem_id=4)
+                # thumbnail = gr.components.Radio(label="是否返回缩略图", choices=["yes", "no"], value="yes", elem_id=4)
+                btn = gr.Button("搜索")
+                # feedback_btn = gr.Radio(label="检索结果反馈",
+                #       choices=['未知(反馈可持续优化LSU🤗)', '准确率低(<30%)', '准确率中(30% ~ 80%)', '准确率高(>80%)',], value='未知(反馈可持续优化LSU🤗)')
+            with gr.Column(scale=100):
+                out = gr.Gallery(label="检索结果为：").style(grid=6, height=200)
+                feedback_btn = gr.Textbox(value="", label="请填写合格图像数", elem_id=0, interactive=True)
+                btn2 = gr.Button("提交")
+            
+        # inputs = [text, num, model, thumbnail]
+        inputs = [model, scene]
+        btn.click(fn=clip_api, inputs=inputs, outputs=[out])
+        btn2.click(feedback, inputs=[feedback_btn, model, scene])
+        # feedback_btn.change(feedback, inputs=feedback_btn)
+        gr.Examples(examples, inputs=inputs)
+    return demo
+
+
+if __name__ == "__main__":
+    with gr.TabbedInterface(
+            [generation_eval()],
+            ["图像生成人工评测"],
+    ) as demo:
+        demo.launch(
+            enable_queue=True,
+            share=True,
+        )