bug fix

app.py

@@ -17,18 +17,21 @@ pipe_text2img = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=to
 # pipe_inpaint = StableDiffusionInpaintPipeline(**pipe_text2img.components)   # not work
 pipe_img2img = StableDiffusionImg2ImgPipeline(**pipe_text2img.components).to(device)
 
-def infer_text2img(prompt, width, height): 
-    output = pipe_text2img(prompt, width=width, height=height, guidance_scale=7.5, num_inference_steps=20,)
-    image = output.images[0]
-    return image
+# def infer_text2img(prompt, guide, steps, width, height): 
+#     output = pipe_text2img(prompt, width=width, height=height, guidance_scale=guide, num_inference_steps=steps,)
+#     image = output.images[0]
+#     return image
 
-def infer_img2img(prompt, width, height, image_in, strength ):
-    init_image = image_in.convert("RGB").resize((width, height))
-    output = pipe_img2img(prompt, init_image=init_image, strength=strength, width=width, height=height, guidance_scale=7.5, num_inference_steps=20)
+def infer_text2img(prompt, guide, steps, width, height, image_in, strength):
+    if image_in is not None:
+        init_image = image_in.convert("RGB").resize((width, height))
+        output = pipe_img2img(prompt, init_image=init_image, strength=strength, width=width, height=height, guidance_scale=guide, num_inference_steps=steps)
+    else:
+        output = pipe_text2img(prompt, width=width, height=height, guidance_scale=guide, num_inference_steps=steps,)
     image = output.images[0]
     return image
 
-def infer_inpaint(prompt, width, height, image_in): 
+def infer_inpaint(prompt, guide, steps, width, height, image_in): 
     init_image = image_in["image"].convert("RGB").resize((width, height))
     mask = image_in["mask"].convert("RGB").resize((width, height))
 
@@ -48,12 +51,14 @@ with gr.Blocks() as demo:
                 ]
     with gr.Row():
         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)')
-            image_in = gr.Image(source='upload', elem_id="image_upload", type="pil", label="参考图")
-            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)')
-            strength = gr.Slider(0, 1.0, value = 0.8, step = 0.1, label = '参考图改变程度(strength)')
+            with gr.Row(scale=0.5, ):
+                image_in = gr.Image(source='upload', elem_id="image_upload", type="pil", label="参考图")
+            with gr.Row(scale=0.5, ):
+                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)')
+                strength = gr.Slider(0, 1.0, value = 0.8, step = 0.05, label = '参考图改变程度(strength)')
             prompt = gr.Textbox(label = '提示词(prompt)')
             submit_btn = gr.Button("生成图像(Generate)")
         
@@ -66,10 +71,7 @@ with gr.Blocks() as demo:
         #     inpaint_btn = gr.Button("图像编辑(Inpaint)")
             # img2img_prompt = gr.Textbox(label = '提示词(prompt)')
             # img2img_btn = gr.Button("图像编辑(Inpaint)")
-        if isinstance(image_in, Image.Image):
-            submit_btn.click(fn = infer_img2img, inputs = [prompt, width, height, image_in, strength], outputs = image_out)
-        else:
-            submit_btn.click(fn = infer_text2img, inputs = [prompt, width, height], outputs = image_out)
+        submit_btn.click(fn = infer_text2img, inputs = [prompt, guide, steps, width, height, image_in, strength], outputs = image_out)
         # inpaint_btn.click(fn = infer_inpaint, inputs = [inpaint_prompt, width, height, image_in], outputs = image_out)
         # img2img_btn.click(fn = infer_img2img, inputs = [img2img_prompt, width, height, image_in], outputs = image_out)
 demo.queue(concurrency_count=10).launch()