tori29umai Fabrice-TIERCELIN commited on
Commit
63bfd3a
1 Parent(s): edcfd06

This PR improves the field labels (#1)

Browse files

- This PR improves the field labels (685881fc9e4a441a439df81b2926a7520015a98c)


Co-authored-by: Fabrice TIERCELIN <[email protected]>

Files changed (1) hide show
  1. app.py +8 -8
app.py CHANGED
@@ -1,7 +1,7 @@
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  import spaces
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  import gradio as gr
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  import torch
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- from diffusers import ControlNetModel, StableDiffusionXLControlNetImg2ImgPipeline, ControlNetModel, AutoencoderKL
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  from PIL import Image
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  import os
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  import time
@@ -95,14 +95,14 @@ class Img2Img:
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  with gr.Blocks(css=css) as demo:
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  with gr.Row():
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  with gr.Column():
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- self.input_image_path = gr.Image(label="input_image", type='filepath')
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- self.prompt = gr.Textbox(label="prompt", lines=3)
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- self.negative_prompt = gr.Textbox(label="negative_prompt", lines=3, value="sketch, lowres, error, extra digit, fewer digits, cropped, worst quality,low quality, normal quality, jpeg artifacts, blurry")
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- prompt_analysis_button = gr.Button("prompt_analysis")
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- self.controlnet_scale = gr.Slider(minimum=0.5, maximum=1.25, value=1.0, step=0.01, label="Lineart_fidelity")
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- generate_button = gr.Button("generate")
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  with gr.Column():
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- self.output_image = gr.Image(type="pil", label="output_image")
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  prompt_analysis_button.click(
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  self.process_prompt_analysis,
 
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  import spaces
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  import gradio as gr
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  import torch
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+ from diffusers import ControlNetModel, StableDiffusionXLControlNetImg2ImgPipeline, AutoencoderKL
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  from PIL import Image
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  import os
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  import time
 
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  with gr.Blocks(css=css) as demo:
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  with gr.Row():
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  with gr.Column():
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+ self.input_image_path = gr.Image(label="Input image", type='filepath')
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+ self.prompt = gr.Textbox(label="Prompt", lines=3)
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+ self.negative_prompt = gr.Textbox(label="Negative prompt", lines=3, value="sketch, lowres, error, extra digit, fewer digits, cropped, worst quality,low quality, normal quality, jpeg artifacts, blurry")
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+ prompt_analysis_button = gr.Button("Prompt analysis")
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+ self.controlnet_scale = gr.Slider(minimum=0.5, maximum=1.25, value=1.0, step=0.01, label="Lineart fidelity")
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+ generate_button = gr.Button(value="Generate", variant="primary")
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  with gr.Column():
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+ self.output_image = gr.Image(type="pil", label="Output image")
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  prompt_analysis_button.click(
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  self.process_prompt_analysis,