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import gradio as gr |
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import numpy as np |
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import colorizers as c |
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from colorizers.util import postprocess_tens, preprocess_img |
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def interface(image, model: str = "siggraph17"): |
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if model == "eccv16": |
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img = siggraph17(pretrained=True).eval() |
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else: |
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img = c.siggraph17(pretrained=True).eval() |
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oimg = np.asarray(image) |
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if(oimg.ndim == 2): |
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oimg = np.tile(oimg[:,:,None], 3) |
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(tens_l_orig, tens_l_rs) = preprocess_img(oimg) |
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output_img = postprocess_tens( |
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tens_l_orig, |
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img(tens_l_rs).cpu() |
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) |
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return output_img |
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css=''' |
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.Box { |
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background-color: var(--color-canvas-default); |
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border-color: var(--color-border-default); |
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border-style: solid; |
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border-width: 1px; |
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border-radius: 6px; |
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} |
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.d-flex { |
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display: flex !important; |
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} |
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.flex-md-row { |
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flex-direction: row !important; |
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} |
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.flex-column { |
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flex-direction: column !important; |
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} |
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''' |
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title = "Image Colorization Using AI Models" |
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description = r"""<center>An automatic colorization functionality for Real-Time User-Guided Image Colorization with Learned Deep Priors,ECCV16 & SIGGRAPH 2017 Models!<br> |
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Practically the algorithm is used to COLORIZE your **old BLACK & WHITE / GRAYSCALE photos**.<br> |
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To use it, simply just upload the concerned image.<br> |
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""" |
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article = r""" |
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""" |
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gr.HTML("""<style>""" + css+ """</Style>""") |
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mainBody = gr.Interface( |
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interface, |
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[ |
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gr.components.Image(type="pil", label="image"), |
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gr.components.Radio( |
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["siggraph17"], |
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type="value", |
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label="model" |
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) |
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], |
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[ |
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gr.components.Image(label="output") |
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], |
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theme="huggingface", |
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title=title, |
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description=description, |
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article=article, |
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live=True, |
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) |
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mainBody.launch() |
