update

DESCRIPTION.md

@@ -0,0 +1 @@
+Recreate the viral AnimeGAN image transformation demo.

README.md

@@ -1,38 +1,11 @@
+
 ---
-title: AnimeGANv2
-emoji: ⚡
-colorFrom: yellow
-colorTo: blue
+title: animeganv2 
+emoji: 🔥
+colorFrom: indigo
+colorTo: indigo
 sdk: gradio
-sdk_version: 3.0.5
-app_file: app.py
+sdk_version: 3.12.0
+app_file: run.py
 pinned: false
 ---
-
-# 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

@@ -1,33 +1,38 @@
+import gradio as gr
 from PIL import Image
 import torch
-import gradio as gr
-
-
 
 model2 = torch.hub.load(
     "AK391/animegan2-pytorch:main",
     "generator",
     pretrained=True,
-    device="cpu",
     progress=False
 )
-
-
-model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1",  device="cpu")
+model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1")
 face2paint = torch.hub.load(
     'AK391/animegan2-pytorch:main', 'face2paint', 
-    size=1024, device="cpu",side_by_side=False
+    size=512,side_by_side=False
 )
+
 def inference(img, ver):
     if ver == 'version 2 (🔺 robustness,🔻 stylization)':
         out = face2paint(model2, img)
     else:
         out = face2paint(model1, img)
     return out
-  
+
 title = "AnimeGANv2"
 description = "Gradio Demo for AnimeGanv2 Face Portrait. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please use a cropped portrait picture for best results similar to the examples below."
 article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
-examples=[['groot.jpeg','version 2 (🔺 robustness,🔻 stylization)'],['bill.png','version 1 (🔺 stylization, 🔻 robustness)'],['tony.png','version 1 (🔺 stylization, 🔻 robustness)'],['elon.png','version 2 (🔺 robustness,🔻 stylization)'],['IU.png','version 1 (🔺 stylization, 🔻 robustness)'],['billie.png','version 2 (🔺 robustness,🔻 stylization)'],['will.png','version 2 (🔺 robustness,🔻 stylization)'],['beyonce.png','version 1 (🔺 stylization, 🔻 robustness)'],['gongyoo.jpeg','version 1 (🔺 stylization, 🔻 robustness)']]
-gr.Interface(inference, [gr.inputs.Image(type="pil"),gr.inputs.Radio(['version 1 (🔺 stylization, 🔻 robustness)','version 2 (🔺 robustness,🔻 stylization)'], type="value", default='version 2 (🔺 robustness,🔻 stylization)', label='version')
-], gr.outputs.Image(type="pil"),title=title,description=description,article=article,examples=examples,allow_flagging=False,allow_screenshot=False).launch()
+examples=[['groot.jpeg','version 2 (🔺 robustness,🔻 stylization)'],['gongyoo.jpeg','version 1 (🔺 stylization, 🔻 robustness)']]
+
+demo = gr.Interface(
+    fn=inference, 
+    inputs=[gr.inputs.Image(type="pil"),gr.inputs.Radio(['version 1 (🔺 stylization, 🔻 robustness)','version 2 (🔺 robustness,🔻 stylization)'], type="value", default='version 2 (🔺 robustness,🔻 stylization)', label='version')], 
+    outputs=gr.outputs.Image(type="pil"),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples)
+
+demo.launch()

run.ipynb

@@ -0,0 +1 @@
+{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: animeganv2\n", "### Recreate the viral AnimeGAN image transformation demo.\n", "        "]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio torch torchvision Pillow gdown numpy scipy cmake onnxruntime-gpu opencv-python-headless"]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/animeganv2/gongyoo.jpeg\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/animeganv2/groot.jpeg"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from PIL import Image\n", "import torch\n", "\n", "model2 = torch.hub.load(\n", "    \"AK391/animegan2-pytorch:main\",\n", "    \"generator\",\n", "    pretrained=True,\n", "    progress=False\n", ")\n", "model1 = torch.hub.load(\"AK391/animegan2-pytorch:main\", \"generator\", pretrained=\"face_paint_512_v1\")\n", "face2paint = torch.hub.load(\n", "    'AK391/animegan2-pytorch:main', 'face2paint', \n", "    size=512,side_by_side=False\n", ")\n", "\n", "def inference(img, ver):\n", "    if ver == 'version 2 (\ud83d\udd3a robustness,\ud83d\udd3b stylization)':\n", "        out = face2paint(model2, img)\n", "    else:\n", "        out = face2paint(model1, img)\n", "    return out\n", "\n", "title = \"AnimeGANv2\"\n", "description = \"Gradio Demo for AnimeGanv2 Face Portrait. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please use a cropped portrait picture for best results similar to the examples below.\"\n", "article = \"<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>\"\n", "examples=[['groot.jpeg','version 2 (\ud83d\udd3a robustness,\ud83d\udd3b stylization)'],['gongyoo.jpeg','version 1 (\ud83d\udd3a stylization, \ud83d\udd3b robustness)']]\n", "\n", "demo = gr.Interface(\n", "    fn=inference, \n", "    inputs=[gr.inputs.Image(type=\"pil\"),gr.inputs.Radio(['version 1 (\ud83d\udd3a stylization, \ud83d\udd3b robustness)','version 2 (\ud83d\udd3a robustness,\ud83d\udd3b stylization)'], type=\"value\", default='version 2 (\ud83d\udd3a robustness,\ud83d\udd3b stylization)', label='version')], \n", "    outputs=gr.outputs.Image(type=\"pil\"),\n", "    title=title,\n", "    description=description,\n", "    article=article,\n", "    examples=examples)\n", "\n", "demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -0,0 +1,38 @@
+import gradio as gr
+from PIL import Image
+import torch
+
+model2 = torch.hub.load(
+    "AK391/animegan2-pytorch:main",
+    "generator",
+    pretrained=True,
+    progress=False
+)
+model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1")
+face2paint = torch.hub.load(
+    'AK391/animegan2-pytorch:main', 'face2paint', 
+    size=512,side_by_side=False
+)
+
+def inference(img, ver):
+    if ver == 'version 2 (🔺 robustness,🔻 stylization)':
+        out = face2paint(model2, img)
+    else:
+        out = face2paint(model1, img)
+    return out
+
+title = "AnimeGANv2"
+description = "Gradio Demo for AnimeGanv2 Face Portrait. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please use a cropped portrait picture for best results similar to the examples below."
+article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
+examples=[['groot.jpeg','version 2 (🔺 robustness,🔻 stylization)'],['gongyoo.jpeg','version 1 (🔺 stylization, 🔻 robustness)']]
+
+demo = gr.Interface(
+    fn=inference, 
+    inputs=[gr.inputs.Image(type="pil"),gr.inputs.Radio(['version 1 (🔺 stylization, 🔻 robustness)','version 2 (🔺 robustness,🔻 stylization)'], type="value", default='version 2 (🔺 robustness,🔻 stylization)', label='version')], 
+    outputs=gr.outputs.Image(type="pil"),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples)
+
+demo.launch()