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# folder where the image is already saved (without bounding boxes)
data_dir = 'media/stable_numbers/number_crops/'

# folder where the new image with bounding boxes should be saved
out_dir = 'media/copy_labeled_number_crops/'

# go through the unique file names (because files can have more than 1 bounding box)
for file in new_df.filename.unique():
    
    # load in the image and .loc[] the rows where it's referenced (each row represents 1 bounding box)

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import pynvml

pynvml.nvmlInit()
handle = pynvml.nvmlDeviceGetHandleByIndex(0)
device_name = pynvml.nvmlDeviceGetName(handle)

if (device_name != b'Tesla T4') and (device_name != b'Tesla P4') and (device_name != b'Tesla P100-PCIE-16GB'):
  raise Exception("""
                     Unfortunately this instance does not have a T4, P4 or P100 GPU.\n
                     Please make sure you've configured Colab to request a GPU instance type.\n

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import os
import urllib

def data_check(file_name, data_dir='', base_url='https://s3.amazonaws.com/nyc-tlc/trip+data/'):
    """
    1. check if the given {file_name} exists locally in {data_dir}
    2. download from {base_url} & save in {data_dir) if not
    
    INPUTS
    > file_name 

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Tested in Ubuntu 16.04 (test machine has GPUs. may need some modification if have no GPU)

How-To-Use:

== 0. Have a working python 3.7.3 with pip ==

== 1. Checkout openpilot ==

cd ~/
git clone -b sim https://github.com/commaai/openpilot.git