add title
Browse files- app.py +38 -16
- log.csv +4 -0
- pikachu.webp +0 -0
- requirements.txt +1 -0
- rhinocorne.webp +0 -0
- tortank.png +0 -0
app.py
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@@ -1,42 +1,64 @@
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../pokemonclassifier.ipynb.
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# %% auto 0
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__all__ = ['modelname', 'pokemon_types', 'pokemon_types_en', '
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'
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# %% ../pokemonclassifier.ipynb 3
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import pandas as pd
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modelname = 'model.pkl'
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pokemon_types = pd.read_csv("pokemongen1patch.csv"
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pokemon_types_en = pokemon_types['en']
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pokemon_types_fr = pokemon_types['fr']
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# %% ../pokemonclassifier.ipynb
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from huggingface_hub import hf_hub_download
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from fastai.learner import load_learner
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learn_inf = load_learner(hf_hub_download("Okkoman/PokeFace", modelname))
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learn_inf.dls.vocab
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imagespath = ''
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# %% ../pokemonclassifier.ipynb
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import gradio as gr
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def classify_image(img):
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prob_threshold = 0.8
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pred,pred_idx,probs = learn_inf.predict(img)
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index = pokemon_types_en[pokemon_types_en == pred].index[0]
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if probs[pred_idx] > prob_threshold:
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return f"{
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else:
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return
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label = gr.outputs.Label()
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examples = [f"{imagespath}pikachu.webp", f"{imagespath}bulbizarre.jpg", f"{imagespath}tortank.png"]
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intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
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intf.launch(inline=False)
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../pokemonclassifier.ipynb.
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# %% auto 0
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__all__ = ['modelname', 'pokemon_types', 'pokemon_types_en', 'learn_inf', 'imagespath', 'lang', 'prob_threshold',
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'classify_image']
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# %% ../pokemonclassifier.ipynb 3
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import pandas as pd
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modelname = 'model.pkl'
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pokemon_types = pd.read_csv("pokemongen1patch.csv")
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pokemon_types_en = pokemon_types['en']
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# %% ../pokemonclassifier.ipynb 27
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from huggingface_hub import hf_hub_download
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from fastai.learner import load_learner
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learn_inf = load_learner(hf_hub_download("Okkoman/PokeFace", modelname))
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imagespath = ''
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# %% ../pokemonclassifier.ipynb 31
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import gradio as gr
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from flask import request
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lang = 'en'
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prob_threshold = 0.75
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if request:
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lang = request.headers.get("Accept-Language")
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if lang == 'fr':
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title = "# PokeFace : Quel est ce pokemon ?"
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description = "## Un classifieur d'images pour les pokemons de 1ere génération (001-151)"
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unknown = 'inconnu'
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else:
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title = "# PokeFace : What is this pokemon ?"
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description = "## An image classifier for 1st generation pokemons (001-151)"
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unknown = 'unknown'
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def classify_image(img):
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pred,pred_idx,probs = learn_inf.predict(img)
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index = pokemon_types_en[pokemon_types_en == pred].index[0]
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label = pokemon_types[lang].iloc[index]
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if probs[pred_idx] > prob_threshold:
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return f"{label} {probs[pred_idx]*100:.0f}%"
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else:
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return unknown
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with gr.Blocks() as demo:
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with gr.Row():
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gr.Markdown(title)
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with gr.Row():
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gr.Markdown(description)
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with gr.Row():
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interf = gr.Interface(
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fn=classify_image,
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inputs=gr.inputs.Image(shape=(192,192)),
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outputs=gr.outputs.Label(),
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examples=imagespath,
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allow_flagging='auto')
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demo.launch(inline=False)
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log.csv
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input
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pikachu.webp
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rhinocorne.webp
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bulbizarre.jpg
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pikachu.webp
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![]() |
![]() |
requirements.txt
CHANGED
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fastai>=2.0.0
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pandas
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flask
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fastai>=2.0.0
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pandas
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rhinocorne.webp
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tortank.png
DELETED
Binary file (106 kB)
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