2024-05-08 14:16:31 +00:00
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Bear Classifier\n",
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"\n",
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"Grizzly, Black, or Teddy Bear?"
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]
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},
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{
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"cell_type": "code",
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2024-05-08 17:48:04 +00:00
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"execution_count": 1,
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2024-05-08 14:16:31 +00:00
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"metadata": {},
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"outputs": [],
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"source": [
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"from fastai.data.all import *\n",
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"from fastai.vision.all import *\n",
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"from fastcore.all import *"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Image Download"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"from duckduckgo_search import DDGS\n",
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"\n",
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"def search_images(search_term, max_images = 100):\n",
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" return L(DDGS().images(search_term, max_results = max_images)).itemgot('image')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"\n",
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"<style>\n",
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" /* Turns off some styling */\n",
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" progress {\n",
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" /* gets rid of default border in Firefox and Opera. */\n",
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" border: none;\n",
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" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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" background-size: auto;\n",
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" }\n",
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" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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" }\n",
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" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
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" background: #F44336;\n",
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" }\n",
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"</style>\n"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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"data": {
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"text/html": [
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"\n",
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" <div>\n",
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" <progress value='335872' class='' max='332689' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
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" 100.96% [335872/332689 00:00<00:00]\n",
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" </div>\n",
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" "
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<PIL.Image.Image image mode=RGB size=256x171>"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from fastdownload import download_url\n",
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"\n",
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"image_urls = search_images('grizzly', max_images = 1)\n",
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"\n",
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"destination = 'bears/grizzly.jpg'\n",
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"download_url(image_urls[0], destination)\n",
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"\n",
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"image = Image.open(destination)\n",
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"image.to_thumb(256, 256)"
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]
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},
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{
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"cell_type": "code",
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2024-05-08 17:48:04 +00:00
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"execution_count": 2,
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2024-05-08 14:16:31 +00:00
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"metadata": {},
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"outputs": [],
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"source": [
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"from pathlib import Path\n",
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2024-05-08 17:48:04 +00:00
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"data_set_path = Path('bears')\n",
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"bear_types = 'grizzly', 'black', 'teddy'"
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2024-05-08 14:16:31 +00:00
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"from fastai.vision.utils import download_images\n",
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"\n",
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"for bear_type in bear_types:\n",
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" destination = data_set_path/bear_type\n",
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" destination.mkdir(exist_ok = True)\n",
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" search_results = search_images(f'{bear_type} bear', max_images = 100)\n",
|
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" download_images(destination, urls = search_results)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Verify Images"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"12"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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|
|
"from fastai.vision.utils import get_image_files, verify_images\n",
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"\n",
|
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|
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"failed_images = verify_images(get_image_files(data_set_path))\n",
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"failed_images.map(Path.unlink)\n",
|
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|
"len(failed_images)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Data Sets"
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]
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},
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{
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"cell_type": "code",
|
2024-05-08 17:48:04 +00:00
|
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"execution_count": 3,
|
2024-05-08 14:16:31 +00:00
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"metadata": {},
|
|
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"outputs": [],
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"source": [
|
|
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|
|
"bears_data = DataBlock(\n",
|
|
|
|
|
" blocks = (ImageBlock, CategoryBlock),\n",
|
|
|
|
|
" get_items = get_image_files,\n",
|
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|
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" splitter = RandomSplitter(valid_pct = 0.2, seed = 42),\n",
|
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|
|
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" get_y = parent_label,\n",
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" item_tfms = Resize(128),\n",
|
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|
" batch_tfms = aug_transforms(mult = 2)\n",
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").dataloaders(data_set_path)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"<Figure size 1200x600 with 8 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"bears_data.train.show_batch(max_n = 8, nrows = 2, unique = True)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Train Model"
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]
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},
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{
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"cell_type": "code",
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2024-05-08 17:48:04 +00:00
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"execution_count": 4,
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2024-05-08 14:16:31 +00:00
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"metadata": {},
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"outputs": [
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"data": {
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"\n",
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" /* Turns off some styling */\n",
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" progress {\n",
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" /* gets rid of default border in Firefox and Opera. */\n",
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" border: none;\n",
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" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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" background-size: auto;\n",
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" }\n",
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" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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" }\n",
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" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
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" background: #F44336;\n",
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" }\n",
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"</style>\n"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/html": [
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: left;\">\n",
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" <th>epoch</th>\n",
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" <th>train_loss</th>\n",
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" <th>valid_loss</th>\n",
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" <th>error_rate</th>\n",
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" <th>time</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <td>0</td>\n",
|
2024-05-08 17:48:04 +00:00
|
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" <td>1.710603</td>\n",
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" <td>0.319241</td>\n",
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" <td>0.134615</td>\n",
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" <td>00:12</td>\n",
|
2024-05-08 14:16:31 +00:00
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" </tr>\n",
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" </tbody>\n",
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"</table>"
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"output_type": "display_data"
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},
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"data": {
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"\n",
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"<style>\n",
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" /* Turns off some styling */\n",
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" progress {\n",
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" /* gets rid of default border in Firefox and Opera. */\n",
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" border: none;\n",
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" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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" background-size: auto;\n",
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" }\n",
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" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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" }\n",
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" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
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" background: #F44336;\n",
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" }\n",
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"</style>\n"
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/html": [
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|
"<table border=\"1\" class=\"dataframe\">\n",
|
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" <thead>\n",
|
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|
|
|
" <tr style=\"text-align: left;\">\n",
|
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|
|
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" <th>epoch</th>\n",
|
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" <th>train_loss</th>\n",
|
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" <th>valid_loss</th>\n",
|
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" <th>error_rate</th>\n",
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" <th>time</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
|
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" <td>0</td>\n",
|
2024-05-08 17:48:04 +00:00
|
|
|
" <td>0.711279</td>\n",
|
|
|
|
|
" <td>0.173566</td>\n",
|
|
|
|
|
" <td>0.057692</td>\n",
|
2024-05-08 14:16:31 +00:00
|
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" <td>00:10</td>\n",
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" </tr>\n",
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" <tr>\n",
|
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" <td>1</td>\n",
|
2024-05-08 17:48:04 +00:00
|
|
|
" <td>0.598342</td>\n",
|
|
|
|
|
" <td>0.062218</td>\n",
|
|
|
|
|
" <td>0.019231</td>\n",
|
2024-05-08 14:16:31 +00:00
|
|
|
" <td>00:10</td>\n",
|
|
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" </tr>\n",
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" <tr>\n",
|
|
|
|
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" <td>2</td>\n",
|
2024-05-08 17:48:04 +00:00
|
|
|
" <td>0.441228</td>\n",
|
|
|
|
|
" <td>0.045272</td>\n",
|
|
|
|
|
" <td>0.019231</td>\n",
|
2024-05-08 14:16:31 +00:00
|
|
|
" <td>00:10</td>\n",
|
|
|
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" </tr>\n",
|
|
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|
" <tr>\n",
|
|
|
|
|
" <td>3</td>\n",
|
2024-05-08 17:48:04 +00:00
|
|
|
" <td>0.366147</td>\n",
|
|
|
|
|
" <td>0.045772</td>\n",
|
|
|
|
|
" <td>0.038462</td>\n",
|
|
|
|
|
" <td>00:09</td>\n",
|
2024-05-08 14:16:31 +00:00
|
|
|
" </tr>\n",
|
|
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|
|
" </tbody>\n",
|
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|
"</table>"
|
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|
],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"model = vision_learner(bears_data, resnet18, metrics = error_rate)\n",
|
|
|
|
|
"model.fine_tune(4)"
|
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|
]
|
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|
},
|
|
|
|
|
{
|
|
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|
"cell_type": "code",
|
2024-05-08 17:48:04 +00:00
|
|
|
"execution_count": 5,
|
2024-05-08 14:16:31 +00:00
|
|
|
"metadata": {},
|
|
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"outputs": [
|
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{
|
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"data": {
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"text/html": [
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"\n",
|
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"<style>\n",
|
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" /* Turns off some styling */\n",
|
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" progress {\n",
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" /* gets rid of default border in Firefox and Opera. */\n",
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" border: none;\n",
|
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|
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
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|
" background-size: auto;\n",
|
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" }\n",
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" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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" }\n",
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" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
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" background: #F44336;\n",
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" }\n",
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"</style>\n"
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],
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2024-05-08 14:16:31 +00:00
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"source": [
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"interpretation = ClassificationInterpretation.from_learner(model)\n",
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"interpretation.plot_confusion_matrix()"
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{
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2024-05-08 17:48:04 +00:00
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2024-05-08 14:16:31 +00:00
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"metadata": {},
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"outputs": [
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2024-05-08 17:48:04 +00:00
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2024-05-08 14:16:31 +00:00
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"text/plain": [
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"<Figure size 1500x300 with 5 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"interpretation.plot_top_losses(5, nrows = 1)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Clean Data Set\n",
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"\n",
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2024-05-08 17:48:04 +00:00
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"The model should be re-trained after this step.\n",
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"\n",
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"It's just helpful to view problematic images and their predictions with a base model."
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]
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},
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{
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"cell_type": "code",
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2024-05-08 17:48:04 +00:00
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"execution_count": 54,
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"metadata": {},
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"outputs": [],
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"source": [
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"for image_file in get_image_files(data_set_path):\n",
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" image = Image.open(image_file)\n",
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" if image.mode != 'RGB':\n",
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" # These image files will fail to be opened with the image cleaner by default.\n",
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" print(image_file)\n",
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" image = image.convert('RGB')\n",
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" image.save(image_file)\n",
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" if image_file.suffix == '.png':\n",
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" print(image_file)\n",
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" image.save(image_file, format = 'JPEG')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"\n",
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"<style>\n",
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" /* Turns off some styling */\n",
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" progress {\n",
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" /* gets rid of default border in Firefox and Opera. */\n",
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" border: none;\n",
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" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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" background-size: auto;\n",
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" }\n",
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" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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" }\n",
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" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
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" background: #F44336;\n",
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" }\n",
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"</style>\n"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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{
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"data": {
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"text/html": [],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/html": [
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"\n",
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"<style>\n",
|
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" /* Turns off some styling */\n",
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" progress {\n",
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" /* gets rid of default border in Firefox and Opera. */\n",
|
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" border: none;\n",
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" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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" background-size: auto;\n",
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" }\n",
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" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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" }\n",
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" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
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" background: #F44336;\n",
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" }\n",
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"</style>\n"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/html": [],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
|
2024-05-08 17:48:04 +00:00
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},
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{
|
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"data": {
|
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|
"application/vnd.jupyter.widget-view+json": {
|
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|
|
"model_id": "5ccb80a0fe004cde8b3e8ac04ccdb82f",
|
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|
|
"version_major": 2,
|
|
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|
"version_minor": 0
|
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},
|
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|
"text/plain": [
|
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|
|
"VBox(children=(Dropdown(options=('black', 'grizzly', 'teddy'), value='black'), Dropdown(options=('Train', 'Val…"
|
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|
|
]
|
|
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},
|
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|
"metadata": {},
|
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"output_type": "display_data"
|
2024-05-08 14:16:31 +00:00
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"from fastai.vision.widgets import ImageClassifierCleaner\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"cleaner = ImageClassifierCleaner(model)\n",
|
|
|
|
|
"cleaner"
|
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|
|
|
]
|
|
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|
|
},
|
|
|
|
|
{
|
|
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|
|
"cell_type": "markdown",
|
|
|
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"metadata": {},
|
|
|
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"source": [
|
|
|
|
|
"## Export Model"
|
|
|
|
|
]
|
|
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|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 10,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"model.export()"
|
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|
]
|
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|
|
}
|
|
|
|
|
],
|
|
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|
"metadata": {
|
|
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|
"kernelspec": {
|
|
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|
|
"display_name": "Python 3",
|
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"language": "python",
|
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"name": "python3"
|
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},
|
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"language_info": {
|
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|
"codemirror_mode": {
|
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|
"name": "ipython",
|
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"version": 3
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},
|
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|
"file_extension": ".py",
|
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"mimetype": "text/x-python",
|
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|
"name": "python",
|
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|
|
"nbconvert_exporter": "python",
|
|
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|
|
"pygments_lexer": "ipython3",
|
|
|
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|
"version": "3.11.5"
|
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|
|
}
|
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},
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"nbformat": 4,
|
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"nbformat_minor": 2
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}
|
