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Build error
Build error
Fix Gradio and dependency compatibility
#1
by Theivaprakasham - opened
- .gitattributes +29 -27
- LICENSE +7 -7
- README.md +13 -13
- __pycache__/app.cpython-312.pyc +0 -0
- app.py +15 -24
- examples/flowers0.jpg +0 -0
- examples/flowers2.jpg +0 -0
- requirements.txt +3 -4
.gitattributes
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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LICENSE
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Copyright 2022 Kurian Benoy
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Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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Copyright 2022 Kurian Benoy
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Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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README.md
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---
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title: Identify Which Flower
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emoji: π
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colorFrom: gray
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colorTo: pink
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sdk: gradio
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sdk_version:
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: Identify Which Flower
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emoji: π
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colorFrom: gray
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colorTo: pink
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sdk: gradio
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sdk_version: 5.29.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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__pycache__/app.cpython-312.pyc
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Binary file (1.84 kB). View file
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app.py
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import gradio as gr
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from huggingface_hub import from_pretrained_fastai
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from fastai.vision.all import *
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learn = from_pretrained_fastai(repo_id)
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labels = learn.dls.vocab
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EXAMPLES_PATH = Path(
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def predict(img):
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img = PILImage.create(img)
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_pred, _pred_w_idx, probs = learn.predict(img)
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return labels_probs
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"title": "Identify which flower it is?",
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"description": "I am terribly bad at remembering names of flowers and trees and it's often difficult to fathom how diverse our natural world is. There are over 5,000 species of mammals, 10,000 species of birds, 30,000 species of fish β and astonishingly, over 400,000 different types of flowers.\n Identify which flower variety it is by uploading your images.",
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"interpretation": "default",
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"layout": "horizontal",
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"allow_flagging": "never",
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"examples": [f'{EXAMPLES_PATH}/{f.name}' for f in EXAMPLES_PATH.iterdir()],
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}
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demo = gr.Interface(
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fn=predict,
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inputs=gr.
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outputs=gr.
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)
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launch_options = {
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"enable_queue": True,
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"share": True,
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}
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demo.launch(**launch_options)
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from pathlib import Path
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import gradio as gr
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from fastai.vision.all import *
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from huggingface_hub import from_pretrained_fastai
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repo_id = "hugginglearners/flowers_101_convnext_model"
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learn = from_pretrained_fastai(repo_id)
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labels = learn.dls.vocab
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EXAMPLES_PATH = Path("./examples")
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def predict(img):
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img = PILImage.create(img)
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_pred, _pred_w_idx, probs = learn.predict(img)
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return {labels[i]: float(probs[i]) for i, _ in enumerate(labels)}
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examples = [str(path) for path in EXAMPLES_PATH.iterdir()] if EXAMPLES_PATH.exists() else None
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demo = gr.Interface(
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fn=predict,
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inputs=gr.Image(type="pil", height=192, width=192),
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outputs=gr.Label(num_top_classes=3),
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title="Identify which flower it is?",
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description="Identify which flower variety it is by uploading an image.",
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examples=examples,
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flagging_mode="never",
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)
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demo.queue().launch(share=False)
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examples/flowers0.jpg
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Git LFS Details
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examples/flowers2.jpg
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Git LFS Details
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requirements.txt
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fastai=
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huggingface_hub[fastai]
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timm==0.6.2.dev0
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fastai>=2.7.18,<3
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huggingface_hub[fastai]>=0.23
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timm==0.6.13
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