Neuronet

import socket,warnings try: socket.setdefaulttimeout(1) socket.socket(socket.AF_INET, socket.SOCK_STREAM).connect(('1.1.1.1', 53)) except socket.error as ex: raise Exception("STOP: No internet. Click '>|' in top right and set 'Internet' switch to on")

import os iskaggle = os.environ.get('KAGGLE_KERNEL_RUN_TYPE', '')

if iskaggle: !pip install -Uqq fastai

!pip install -Uqq duckduckgo_search

from duckduckgo_search import ddg_images from fastcore.all import *

def search_images(term, max_images=200): return L(ddg_images(term, max_results=max_images)).itemgot('image')

urls = search_images(' star fox photos', max_images=1) urls[0]

from fastdownload import download_url dest = 'starfox.jpg' download_url(urls[0], dest, show_progress=False)

from fastai.vision.all import * im = Image.open(dest) im.to_thumb(256,256)

download_url(search_images('eva 01', max_images=1)[0], 'forest.jpg', show_progress=False) Image.open('forest.jpg').to_thumb(256,256)

searches = 'eva 01','star fox' path = Path('eva 01_or_not') from time import sleep

for o in searches: dest = (path/o) dest.mkdir(exist_ok=True, parents=True) download_images(dest, urls=search_images(f'{o} photo')) sleep(10) # Pause between searches to avoid over-loading server download_images(dest, urls=search_images(f'{o} sun photo')) sleep(10) download_images(dest, urls=search_images(f'{o} shade photo')) sleep(10) resize_images(path/o, max_size=400, dest=path/o)

failed = verify_images(get_image_files(path)) failed.map(Path.unlink) len(failed)

dls = DataBlock( blocks=(ImageBlock, CategoryBlock), get_items=get_image_files, splitter=RandomSplitter(valid_pct=0.2, seed=42), get_y=parent_label, item_tfms=[Resize(192, method='squish')] ).dataloaders(path)

dls.show_batch(max_n=6)

learn = vision_learner(dls, resnet18, metrics=error_rate) learn.fine_tune(3)

is_bird,_,probs = learn.predict(PILImage.create('bird.jpg')) print(f"This is a: {is_bird}.") print(f"Probability it's a bird: {probs[0]:.4f}")