Commit 4d630046 authored by bryandlee's avatar bryandlee

Demo: Update docs

parent c28b876f
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more about facegan here: https://github.com/bryandlee/animegan2-pytorch\n","\n","To start using this, run the cells with `Ctrl+F9` or \"Runtime > Run All\"\n","\n","For accelerated inference, you can use a GPU. Simply select \"Runtime > Change runtime type\" and select \"GPU\" in the \"Hardware Acceleration\" dropdown.\n","\n"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":621,"referenced_widgets":["7d864c45136c4c38af6c30598c2cb600","7b277e997d7f47da9c9be52de68b0c63","63a12ba1408048778f2b81218edf4194","f55b447ca89d4c38aa6214b201e7eb70","546b62f8fb4c4966b4c40cf204992d6a","ddbd5c05a3184b78bcc734864ce0e45e","84a65ad31bcb46298d58cf63c3d0d459","19b78e9b0625445a9efe84268ae05e49","be9ca13247a34654a65b5979b9d585e1","a7d105fc061f426f9884680fce193647","1515797846924532b33ae675aeaf3093","b48aa4b5d2d5470cb298e4fcfa9ded33","b22e6372922f434aaae9c0b6ddb81b2d","87c59a4e4c6f47c7936d61481fb52124","2158cacf4e6e479faa44e91ca12bbda7","23ee9829bfa04e8f8435a8ae476b43d1","736138a274cc431b943753e139c6523f","7cc2c98cd6a04949b48142f3e403b08a","99b447095ace462fbd5e1a623b28fe66","b2ca4deaa28c4e18936a84732be18884","8f5c711475c843e483701e09749c43a0","35b94797d82f40c29e9197ccb87bad9b","7d1abcf6f60e4fd98837fcc9ba50568b","23bb16852e60478b834a38bd59459af8","e099c93cc8d54f5eb503228904b5e579","941adc4eddd34b9e9273a9380858b109","ffe6eb4cc7da4251b4e31cd4e653b226","9fcac464ab454bf1a578b8966650812a","daf001934c554c508c823f4a2c76a387","9724a26695f0402bbc97810ed4aa454c","d2af4b7d511b41f7892eb9c8e800fed9","651969adccb94dc7b6656ed2c9b281fb"]},"cellView":"form","id":"VSdphHwYzwkY","executionInfo":{"status":"ok","timestamp":1636402044617,"user_tz":300,"elapsed":328,"user":{"displayName":"Xing Han Lu","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj1JLJ4-51nkV6evLzf5UzitxpKQWI2DzQiOOy0=s64","userId":"00576115525065362925"}},"outputId":"6c236705-9d51-474a-8632-902b43644fc0"},"source":["from io import BytesIO\n","import torch\n","from PIL import Image\n","\n","import ipywidgets as widgets\n","import IPython.display as display\n","from google.colab import files\n","\n","device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n","model = torch.hub.load(\"bryandlee/animegan2-pytorch:main\", \"generator\", device=device).eval()\n","face2paint = torch.hub.load(\"bryandlee/animegan2-pytorch:main\", \"face2paint\", device=device)\n","\n","#@title Anime FaceGAN Colab app\n","image_format = \"jpeg\" #@param [\"jpeg\", \"png\"]\n","\n","\n","button = widgets.Button(description=\"Start\")\n","output = widgets.Output()\n","\n","uploader = widgets.FileUpload(\n"," accept='image/*', # Accepted file extension e.g. '.txt', '.pdf', 'image/*', 'image/*,.pdf'\n"," multiple=False # True to accept multiple files upload else False\n",")\n","\n","def run(b):\n"," button.disabled = True\n","\n"," with output:\n"," display.clear_output()\n","\n"," for fname in uploader.value:\n"," bytes_in = uploader.value[fname]['content']\n","\n"," im_in = Image.open(BytesIO(bytes_in)).convert(\"RGB\")\n"," im_out = face2paint(model, im_in, side_by_side=False)\n","\n"," buffer_out = BytesIO()\n"," im_out.save(buffer_out, format=image_format)\n","\n"," bytes_out = buffer_out.getvalue()\n"," wi1 = widgets.Image(value=bytes_in, format=image_format)\n"," wi2 = widgets.Image(value=bytes_out, format=image_format)\n","\n"," wi1.layout.max_width = '500px'\n"," wi1.layout.max_height = '500px'\n"," wi2.layout.max_width = '500px'\n"," wi2.layout.max_height = '500px'\n","\n"," ## Side by side thanks to HBox widgets\n"," sidebyside = widgets.HBox([wi1, wi2])\n"," ## Finally, show.\n"," with output:\n"," display.display(sidebyside)\n"," \n"," button.disabled = False\n","\n","button.on_click(run)\n","display.display(uploader, button, output)"],"execution_count":3,"outputs":[{"output_type":"stream","name":"stderr","text":["Using cache found in /root/.cache/torch/hub/bryandlee_animegan2-pytorch_main\n","Using cache found in /root/.cache/torch/hub/bryandlee_animegan2-pytorch_main\n"]},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"7d864c45136c4c38af6c30598c2cb600","version_minor":0,"version_major":2},"text/plain":["FileUpload(value={}, accept='image/*', description='Upload')"]},"metadata":{}},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"f55b447ca89d4c38aa6214b201e7eb70","version_minor":0,"version_major":2},"text/plain":["Button(description='Start', style=ButtonStyle())"]},"metadata":{}},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"84a65ad31bcb46298d58cf63c3d0d459","version_minor":0,"version_major":2},"text/plain":["Output()"]},"metadata":{}}]}]} {
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"source": [
"Interactive Demo for AnimeGANv2:FacePortraitv2 created by @xhlulu\n",
"\n",
"Learn more about the model here: https://github.com/bryandlee/animegan2-pytorch\n",
"\n",
"To start using this, run the cells with `Ctrl+F9` or \"Runtime > Run All\"\n",
"\n",
"For accelerated inference, you can use a GPU. Simply select \"Runtime > Change runtime type\" and select \"GPU\" in the \"Hardware Acceleration\" dropdown.\n"
]
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"status": "ok",
"timestamp": 1636402044617,
"user": {
"displayName": "Xing Han Lu",
"photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gj1JLJ4-51nkV6evLzf5UzitxpKQWI2DzQiOOy0=s64",
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"from io import BytesIO\n",
"import torch\n",
"from PIL import Image\n",
"\n",
"import ipywidgets as widgets\n",
"import IPython.display as display\n",
"from google.colab import files\n",
"\n",
"device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
"model = torch.hub.load(\"bryandlee/animegan2-pytorch:main\", \"generator\", device=device).eval()\n",
"face2paint = torch.hub.load(\"bryandlee/animegan2-pytorch:main\", \"face2paint\", device=device)\n",
"\n",
"#@title Anime FaceGAN Colab app\n",
"image_format = \"jpeg\" #@param [\"jpeg\", \"png\"]\n",
"\n",
"\n",
"button = widgets.Button(description=\"Start\")\n",
"output = widgets.Output()\n",
"\n",
"uploader = widgets.FileUpload(\n",
" accept='image/*', # Accepted file extension e.g. '.txt', '.pdf', 'image/*', 'image/*,.pdf'\n",
" multiple=False # True to accept multiple files upload else False\n",
")\n",
"\n",
"def run(b):\n",
" button.disabled = True\n",
"\n",
" with output:\n",
" display.clear_output()\n",
"\n",
" for fname in uploader.value:\n",
" bytes_in = uploader.value[fname]['content']\n",
"\n",
" im_in = Image.open(BytesIO(bytes_in)).convert(\"RGB\")\n",
" im_out = face2paint(model, im_in, side_by_side=False)\n",
"\n",
" buffer_out = BytesIO()\n",
" im_out.save(buffer_out, format=image_format)\n",
"\n",
" bytes_out = buffer_out.getvalue()\n",
" wi1 = widgets.Image(value=bytes_in, format=image_format)\n",
" wi2 = widgets.Image(value=bytes_out, format=image_format)\n",
"\n",
" wi1.layout.max_width = '500px'\n",
" wi1.layout.max_height = '500px'\n",
" wi2.layout.max_width = '500px'\n",
" wi2.layout.max_height = '500px'\n",
"\n",
" ## Side by side thanks to HBox widgets\n",
" sidebyside = widgets.HBox([wi1, wi2])\n",
" ## Finally, show.\n",
" with output:\n",
" display.display(sidebyside)\n",
" \n",
" button.disabled = False\n",
"\n",
"button.on_click(run)\n",
"display.display(uploader, button, output)"
]
}
],
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"name": "Anime Facegan.ipynb",
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