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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from fastai import *\n",
"from fastbook import *"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!kaggle datasets download -d gpiosenka/musical-instruments-image-classification"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!ls -l"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!unzip -d images musical-instruments-image-classification.zip"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"path = Path('images')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"path.absolute()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from fastai.vision.all import *\n",
"from fastai.vision.widgets import *"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"csv_path = Path('instruments.csv')\n",
"csv_path.absolute()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dls = ImageDataLoaders.from_csv(path=path,csv_fname='instruments.csv')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"learner = vision_learner(dls=dls,arch=resnet18,metrics=error_rate)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"learner.fine_tune(2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"interp = ClassificationInterpretation.from_learner(learner)\n",
"interp.plot_confusion_matrix()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"interp.plot_top_losses(10,nrows=5, figsize=(15,10))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"cleaner = ImageClassifierCleaner(learner)\n",
"cleaner"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for idx in cleaner.delete(): cleaner.fns[idx].unlink()\n",
"for idx,cat in cleaner.change(): shutil.move(str(cleaner.fns[idx]),path/changed)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"uploader=SimpleNamespace(data=['images/6 test samples/1.jpg'])\n",
"img = (PILImage.create(uploader.data[0])).to_thumb(224)\n",
"img"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"learner.predict(img)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"learner.export('model.pkl')"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"total 46032\n",
"-rwxrwxrwx 1 tux tux 243 Jun 22 21:11 README.md\n",
"-rwxrwxrwx 1 tux tux 3162 Jun 29 16:56 app.ipynb\n",
"-rwxrwxrwx 1 tux tux 970 Jun 22 21:45 app.py\n",
"-rwxrwxrwx 1 tux tux 37139 Jun 22 21:35 banjo.jpg\n",
"-rwxrwxrwx 1 tux tux 47081297 Jun 22 21:08 model.pkl\n",
"-rwxrwxrwx 1 tux tux 6 Jun 22 23:35 requirements.txt\n",
"-rwxrwxrwx 1 tux tux 3774 Jun 29 16:56 train.ipynb\n"
]
}
],
"source": [
"!ls -l"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.10"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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