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The Car Connection Picture
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update dataset overview and ba...
a8d04f5·
Feb 10, 2022 7:44 AM
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Overview

The Car Connection Picture Dataset is a dataset for car classificatioin.

Instruction

HOW TO RUN

  1. Copy all .py files into a folder.
    • Make sure you have all the dependencies installed and up to date (e.g., bs4, requests, etc).
  2. In main.py set path to where the files are, and directory where you want the images to land
    • You do not need to create the directory yourself
  3. Runmain.py. I suggest you try it with a portion of the data first, in case an error emerges later.
    • For instance, in scrape.py line 27, replace for make in listed: to for make in listed[1:3]:

EXAMPLE. Example — Audi vs BMW ConvNet.ipynb : example of a deep learning classification task with Pytorch

WARNING: You may have issues if you use Python 3.6

FAQ

  1. How do I get the large pictures?
    • In scrape.py, row 68, change this line:
    • for ix, photo in enumerate(re.findall('sml.+?_s.jpg', fetch_pics_url)[:150], 1):
    • to this line:
    • for ix, photo in enumerate(re.findall('lrg.+?_l.jpg', fetch_pics_url)[:150], 1):
    • You can use sml, med, lrg for your preferred image size

FILES

FILESDESCRIPTIONEXPORT
scrape.pyCreates a df of all cars with their specs/pics URLsspecs-and-pics.csv
tag.pyTurns the previous df into one tag per URLid_and_pic_url.csv
save.pyTurns all rows in the previous df to a picture named with the tagpictures/*.jpg
select.pyUses numpy to delete interior pictures, based on pixel colorexterior/*.jpg
main.pyRuns all other filesNone
Data Preview
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🎉Many thanks to Graviti Open Datasets for contributing the dataset
Basic Information
Application ScenariosVehicle
AnnotationsClassification
TasksNot Available
LicenseUnknown
Updated on2022-02-10 07:44:41
Metadata
Data TypeImage
Data Volume64,467
Annotation Amount64,467
File Size571.20MB
Copyright Owner
Nicolas Gervais
Annotator
Unknown