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| import os | |
| import gradio as gr | |
| from background_replacer import replace_background | |
| developer_mode = os.getenv('DEV_MODE', False) | |
| DEFAULT_POSITIVE_PROMPT = "on the pavement, poolside, idyllic infinity pool, Hawaiian hilltops, commercial product photography" | |
| DEFAULT_NEGATIVE_PROMPT = "" | |
| EXAMPLES = [] | |
| INTRO = "Test." | |
| def generate( | |
| image, | |
| positive_prompt, | |
| negative_prompt, | |
| seed, | |
| depth_map_feather_threshold, | |
| depth_map_dilation_iterations, | |
| depth_map_blur_radius, | |
| progress=gr.Progress(track_tqdm=True) | |
| ): | |
| if image is None: | |
| return [None, None, None, None] | |
| options = { | |
| 'seed': seed, | |
| 'depth_map_feather_threshold': depth_map_feather_threshold, | |
| 'depth_map_dilation_iterations': depth_map_dilation_iterations, | |
| 'depth_map_blur_radius': depth_map_blur_radius, | |
| } | |
| return replace_background(image, positive_prompt, negative_prompt, options) | |
| custom_css = """ | |
| #image-upload { | |
| flex-grow: 1; | |
| } | |
| #params .tabs { | |
| display: flex; | |
| flex-direction: column; | |
| flex-grow: 1; | |
| } | |
| #params .tabitem[style="display: block;"] { | |
| flex-grow: 1; | |
| display: flex !important; | |
| } | |
| #params .gap { | |
| flex-grow: 1; | |
| } | |
| #params .form { | |
| flex-grow: 1 !important; | |
| } | |
| #params .form > :last-child{ | |
| flex-grow: 1; | |
| } | |
| .md ol, .md ul { | |
| margin-left: 1rem; | |
| } | |
| .md img { | |
| margin-bottom: 1rem; | |
| } | |
| """ | |
| with gr.Blocks(css=custom_css) as iface: | |
| gr.Markdown(INTRO) | |
| with gr.Row(): | |
| with gr.Column(): | |
| image_upload = gr.Image( | |
| label="Product image", | |
| type="pil", | |
| elem_id="image-upload" | |
| ) | |
| caption = gr.Label( | |
| label="Caption", | |
| visible=developer_mode | |
| ) | |
| with gr.Column(elem_id="params"): | |
| with gr.Tab('Prompts'): | |
| positive_prompt = gr.Textbox( | |
| label="Positive Prompt: describe what you'd like to see", | |
| lines=3, | |
| value=DEFAULT_POSITIVE_PROMPT | |
| ) | |
| negative_prompt = gr.Textbox( | |
| label="Negative Prompt: describe what you want to avoid", | |
| lines=3, | |
| value=DEFAULT_NEGATIVE_PROMPT | |
| ) | |
| if developer_mode: | |
| with gr.Tab('Options'): | |
| seed = gr.Number( | |
| label="Seed", | |
| precision=0, | |
| value=0, | |
| elem_id="seed", | |
| visible=developer_mode | |
| ) | |
| depth_map_feather_threshold = gr.Slider( | |
| label="Depth map feather threshold", | |
| value=128, | |
| minimum=0, | |
| maximum=255, | |
| visible=developer_mode | |
| ) | |
| depth_map_dilation_iterations = gr.Number( | |
| label="Depth map dilation iterations", | |
| precision=0, | |
| value=10, | |
| minimum=0, | |
| visible=developer_mode | |
| ) | |
| depth_map_blur_radius = gr.Number( | |
| label="Depth map blur radius", | |
| precision=0, | |
| value=10, | |
| minimum=0, | |
| visible=developer_mode | |
| ) | |
| else: | |
| seed = gr.Number(value=-1, visible=False) | |
| depth_map_feather_threshold = gr.Slider( | |
| value=128, visible=False) | |
| depth_map_dilation_iterations = gr.Number( | |
| precision=0, value=10, visible=False) | |
| depth_map_blur_radius = gr.Number( | |
| precision=0, value=10, visible=False) | |
| gen_button = gr.Button(value="Generate!", variant="primary") | |
| with gr.Tab('Results'): | |
| results = gr.Gallery( | |
| show_label=False, | |
| object_fit="contain", | |
| columns=4 | |
| ) | |
| if developer_mode: | |
| with gr.Tab('Generated'): | |
| generated = gr.Gallery( | |
| show_label=False, | |
| object_fit="contain", | |
| columns=4 | |
| ) | |
| with gr.Tab('Pre-processing'): | |
| pre_processing = gr.Gallery( | |
| show_label=False, | |
| object_fit="contain", | |
| columns=4 | |
| ) | |
| else: | |
| generated = gr.Gallery(visible=False) | |
| pre_processing = gr.Gallery(visible=False) | |
| gr.Examples( | |
| examples=EXAMPLES, | |
| inputs=[image_upload, positive_prompt, negative_prompt], | |
| ) | |
| gen_button.click( | |
| fn=generate, | |
| inputs=[ | |
| image_upload, | |
| positive_prompt, | |
| negative_prompt, | |
| seed, | |
| depth_map_feather_threshold, | |
| depth_map_dilation_iterations, | |
| depth_map_blur_radius | |
| ], | |
| outputs=[ | |
| results, | |
| generated, | |
| pre_processing, | |
| caption | |
| ], | |
| ) | |
| iface.queue(max_size=10, api_open=False).launch(show_api=False) | |