Update app.py

app.py

@@ -3,8 +3,8 @@ import os
 import gradio as gr
 from transformers import pipeline
 
-from diffusers import StableDiffusionPipeline
-import torch
+# from diffusers import StableDiffusionPipeline
+# import torch
 
 
 sd_description = "文字生成图片"
@@ -17,19 +17,19 @@ examples = [[os.path.join(os.path.dirname(__file__), "lion.jpg")], [os.path.join
 app = gr.Interface.from_pipeline(pipe, examples=examples, title='图片识别')
 
 
-model_id = "dreamlike-art/dreamlike-photoreal-2.0"
-pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
-pipe_v1 = pipe.to("cpu")
+# model_id = "dreamlike-art/dreamlike-photoreal-2.0"
+# pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
+# pipe_v1 = pipe.to("cpu")
 
 
-def generate_image_v1(prompt):
-    return pipe_v1(prompt).images[0]
+# def generate_image_v1(prompt):
+#     return pipe_v1(prompt).images[0]
 
-examples = [["落日"], ["沙滩"]]
-app_v1 = gr.Interface(fn=generate_image_v1, inputs="text", outputs="image", examples=examples)
+# examples = [["落日"], ["沙滩"]]
+# app_v1 = gr.Interface(fn=generate_image_v1, inputs="text", outputs="image", examples=examples)
 
 
-demo = gr.TabbedInterface([sd_demo, app, app_v1], ["文字生成图片", "图片识别", "文字生成图片v1"])
+demo = gr.TabbedInterface([sd_demo, app], ["文字生成图片", "图片识别"])
 
 
 demo.launch()