Duplicate from liliyRehtina/AnimeGAN

.gitattributes

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README.md

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+---
+title: AnimeGANv2
+emoji: ⚡
+colorFrom: yellow
+colorTo: blue
+sdk: gradio
+sdk_version: 3.0.5
+app_file: app.py
+pinned: false
+duplicated_from: liliyRehtina/AnimeGAN
+---
+
+# Configuration
+
+`title`: _string_  
+Display title for the Space
+
+`emoji`: _string_  
+Space emoji (emoji-only character allowed)
+
+`colorFrom`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`colorTo`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`sdk`: _string_  
+Can be either `gradio` or `streamlit`
+
+`sdk_version` : _string_  
+Only applicable for `streamlit` SDK.  
+See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
+
+`app_file`: _string_  
+Path to your main application file (which contains either `gradio` or `streamlit` Python code).  
+Path is relative to the root of the repository.
+
+`pinned`: _boolean_  
+Whether the Space stays on top of your list.

app.py

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+from PIL import Image
+import torch
+import gradio as gr
+# Загрузка моделей с разными вариантами настроек
+model1 = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="celeba_distill")
+model2 = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1")
+model3 = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v2")
+model4 = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="paprika")
+def load_face2paint_model(size):
+    global face2paint
+    if size == 512:
+        face2paint = torch.hub.load('bryandlee/animegan2-pytorch:main', 'face2paint',
+                                    size=size, device="cpu", side_by_side=False)
+    elif size == 1024:
+        face2paint = torch.hub.load("bryandlee/animegan2-pytorch:main", "face2paint",
+                                    size=size, device="cpu", side_by_side=False)
+load_face2paint_model(512)  # Загрузка модели с размером 512 по умолчанию
+def inference(img, ver, size):
+    if size != 512:
+        load_face2paint_model(size)  # Загрузка модели с выбранным размером
+    if ver == 'Стиль - 1':
+        out = face2paint(model1, img)
+    elif ver == 'Стиль - 2':
+        out = face2paint(model2, img)
+    elif ver == 'Стиль - 3':
+        out = face2paint(model3, img)
+    elif ver == 'Стиль - 4':
+        out = face2paint(model4, img)
+    return out
+title = "Фото в Рисунок"
+description = "Загрузите картинку любого размера до 1024px, выберите один из форматов генерации, выходной размер и нажмите кнопку Исполнить"
+article = "<br><br><br><br><br>"
+# Создание интерфейса Gradio с вариантами моделей, стилей и размеров и черным фоном
+interface = gr.Interface(inference,
+                         [gr.inputs.Image(type="pil"),
+                          gr.inputs.Radio(['Стиль - 1', 'Стиль - 2', 'Стиль - 3', 'Стиль - 4'],
+                                         type="value",
+                                         default='Стиль - 1',
+                                         label='Выбор стиля'),
+                          gr.inputs.Radio([512, 1024],
+                                         type="value",
+                                         default=512,
+                                         label='Выходной размер')],
+                    gr.outputs.Image(type="pil"),
+              title=title,
+              description=description,
+              article=article,
+              allow_flagging=False,
+              allow_screenshot=False).launch()

requirements.txt

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+torch
+torchvision
+Pillow
+gdown
+numpy
+scipy
+cmake
+onnxruntime-gpu
+opencv-python-headless