new gradio ui with examples

app.py

@@ -6,7 +6,6 @@ from diffusers import StableDiffusionPipeline
 device="cuda"
 model_id = "IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1"
 
-# pipe_img2img = StableDiffusionImg2ImgPipeline.from_pretrained(model_id, tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, unet=unet).to(device)
 pipe_text2img = StableDiffusionPipeline.from_pretrained(model_id).to(device)
 
 def resize(w_val,l_val,img):
@@ -20,12 +19,28 @@ def infer(prompt, guide, steps, width, height):
     image = output.images[0]
     return image
 
-gr.Interface(fn=infer, inputs=
-    [
-        # gr.Image(source="upload", type="filepath", label="原始图像"), 
-        gr.Textbox(label = '提示词(prompt)'),
-        gr.Slider(2, 15, value = 7, label = '文本引导强度(guidance scale)'),
-        gr.Slider(10, 30, value = 20, step = 1, label = '迭代次数(inference steps)'),
-        gr.Slider(256, 768, value = 512, step = 64, label = '宽度(width)'),
-        gr.Slider(256, 768, value = 512, step = 64, label = '高度(height)'),
-    ],outputs='image').queue(concurrency_count=10).launch()
+with gr.Blocks() as demo:
+    examples = [
+                ["飞流直下三千尺, 疑是银河落九天, 瀑布, 插画"], 
+                ["东临碣石, 以观沧海, 波涛汹涌, 插画"], 
+                ["孤帆远影碧空尽，惟见长江天际流,油画"],
+                ["女孩背影, 日落, 唯美插画"],
+                ]
+    with gr.Row():
+        with gr.Column(scale=2, ):
+            output = gr.Image(label = '输出(output)')
+        
+        with gr.Column(scale=1, ):
+            guide = gr.Slider(2, 15, value = 7, label = '文本引导强度(guidance scale)')
+            steps = gr.Slider(10, 30, value = 20, step = 1, label = '迭代次数(inference steps)')
+            width = gr.Slider(256, 768, value = 512, step = 64, label = '宽度(width)')
+            height = gr.Slider(256, 768, value = 512, step = 64, label = '高度(height)')
+            
+            prompt = gr.Textbox(label = '提示词(prompt)')
+            submit_btn = gr.Button("生成图片(Generate)").style(margin=False, rounded=(False, True, True, False), full_width=False,)
+
+            ex = gr.Examples(examples, fn=infer, inputs=[prompt, guide, steps, width, height], outputs=output)
+
+        submit_btn.click(fn = infer, inputs = [prompt, guide, steps, width, height], outputs = output)
+        
+demo.queue(concurrency_count=10).launch()