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import os |
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import sys |
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import face_detection |
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import PIL |
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from PIL import Image, ImageOps |
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import numpy as np |
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import torch |
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torch.set_grad_enabled(False) |
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net = torch.jit.load('dragness_p2s2p_torchscript_cpu.pt') |
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net.eval() |
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def tensor2im(var): |
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var = var.cpu().detach().transpose(0, 2).transpose(0, 1).numpy() |
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var = ((var + 1) / 2) |
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var[var < 0] = 0 |
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var[var > 1] = 1 |
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var = var * 255 |
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return Image.fromarray(var.astype('uint8')) |
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def image_as_array(image_in): |
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im_array = np.array(image_in, np.float32) |
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im_array = (im_array/255)*2 - 1 |
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im_array = np.transpose(im_array, (2, 0, 1)) |
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im_array = np.expand_dims(im_array, 0) |
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return im_array |
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def find_aligned_face(image_in, size=256): |
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aligned_image, n_faces, quad = face_detection.align(image_in, face_index=0, output_size=size) |
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return aligned_image, n_faces, quad |
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def align_first_face(image_in, size=256): |
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aligned_image, n_faces, quad = find_aligned_face(image_in,size=size) |
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if n_faces == 0: |
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image_in = image_in.resize((size, size)) |
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im_array = image_as_array(image_in) |
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else: |
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im_array = image_as_array(aligned_image) |
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return im_array |
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import gradio as gr |
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def face2drag( |
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img: Image.Image, |
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size: int |
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) -> Image.Image: |
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aligned_img = align_first_face(img) |
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input = torch.Tensor(aligned_img) |
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output = net(input) |
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output = tensor2im(output[0]) |
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return output |
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import os |
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import collections |
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from typing import Union, List |
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import numpy as np |
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from PIL import Image |
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import PIL.Image |
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import PIL.ImageFile |
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import numpy as np |
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import scipy.ndimage |
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import requests |
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def inference(img): |
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out = face2drag(img, 256) |
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return out |
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title = "Dragness" |
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description = "Gradio demo for Drag finetuned Pixel2Style2Pixel. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below." |
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article = "<p style='text-align: center'><a href='https://github.com/justinpinkney/pixel2style2pixel/tree/nw' target='_blank'>Github Repo</a></p><p style='text-align: center'>samples: <img src='Sample00001.jpg' alt='Sample00001'/><img src='Sample00002.jpg' alt='Sample00002'/><img src='Sample00003.jpg' alt='Sample00003'/><img src='Sample00004.jpg' alt='Sample00004'/><img src='Sample00005.jpg' alt='Sample00005'/><img src='Sample00006.jpg' alt='Sample00006'/></p><p>Drag model was fine tuned by Doron Adler</p>" |
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examples=[['Example00001.jpg'],['Example00002.jpg'],['Fiona-Example00003.jpg'],['Example00004.jpg'],['Example00005.jpg'],['Example00006.jpg'],['Example00007.jpg']] |
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gr.Interface(inference, gr.inputs.Image(type="pil",shape=(256,256)), gr.outputs.Image(type="pil"),title=title,description=description,article=article,examples=examples,enable_queue=True).launch() |
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