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def generateImagesOfVariousSizes(numberOfPoints):
    directory = 'data/countingVariousSizes/' + str(numberOfPoints) + '/'
    os.makedirs(directory, exist_ok=True)
    
    #Create 5,000 images of this class
    for j in tnrange(5000):
        path = directory + str(j) + '.png'
        #Get points
        x, y = createNonOverlappingPoints(numberOfPoints)
        #Create plot

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learner = create_cnn(data, models.resnet34, metrics=error_rate)
learner.fit_one_cycle(15, max_lr=slice(1e-4, 1e-2))

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learner = create_cnn(data, models.resnet34, metrics=error_rate)
learner.fit_one_cycle(3)

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path = 'data/counting'
np.random.seed(42)
data = ImageDataBunch.from_folder(path, train=".", valid_pct=0.2,
        ds_tfms=get_transforms(), size=224, num_workers=4).normalize(imagenet_stats)
data.show_batch(rows=3, figsize=(7,8))

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learner = create_cnn(data, models.resnet34, metrics=error_rate)
learner.fit_one_cycle(3)

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path = 'data/counting'
data = ImageDataBunch.from_folder(path, train=".", valid_pct=0.2,
        ds_tfms=get_transforms(), size=224, num_workers=4).normalize(imagenet_stats)
data.show_batch(rows=3, figsize=(7,8))

JoshVarty

import random
import numpy as np
import matplotlib.pyplot as plt

def createNonOverlappingPoints(numElements):
    x = np.zeros((numElements)) + 2  #Place the cirlces offscreen
    y = np.zeros((numElements)) + 2  #Place the circles offscreen
    
    for i in range(0, numElements):
        

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learner.fit_one_cycle(15, max_lr=slice(1e-4))

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learner.save('stage-1')
learner.unfreeze()
learner.lr_find()
learner.recorder.plot()

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learner = create_cnn(data, models.resnet34, metrics=error_rate)
learner.fit_one_cycle(5)