fiftyone | source tool for building | Machine Learning library

from fiftyone import ViewField as F

class_name = "Vehicle registration plate"

# Find samples that have a "Vehicle registration plate"
pos_view = dataset.filter_labels("positive_labels", F("label")==class_name)

# Find all samples that do

import fiftyone as fo

# The Dataset or DatasetView containing the samples you wish to draw
dataset_or_view = fo.Dataset(...)

# The directory to which to write the annotated media
output_dir = "/path/for/output"

# The list of `Label` fie

import os

import cv2
import numpy as np

def extract_classwise_instances(samples, output_dir, label_field, ext=".png"):
    print("Extracting object instances...")
    for sample in samples.iter_samples(progress=True):
        img = cv2.i

number_names = ['zero', 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine', 'ten']
# and so on for all numbers

print(number_names[0]) # prints 'zero'
print(number_names[5]) # prints 'five'
print