| OpenCV 3.4.8 Open Source Computer Vision

Classes | Enumerations
Pedestrian Detection
Framework for working with different datasets

## Classes
class | cv::datasets::PD_caltech
struct | cv::datasets::PD_caltechObj
class | cv::datasets::PD_inria
struct | cv::datasets::PD_inriaObj

## Enumerations
enum | cv::datasets::sampleType { cv::datasets::POS = 0, cv::datasets::NEG = 1 }

## Detailed Description

### Caltech Pedestrian Detection Benchmark

Implements loading dataset:

"Caltech Pedestrian Detection Benchmark": http://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/

Note
  First version of Caltech Pedestrian dataset loading. Code to unpack all frames from seq files commented as their number is huge! So currently load only meta information without data. Also ground truth isn't processed, as need to convert it from mat files first.

Usage:

1. From link above download dataset files: `set00.tar`-`set10.tar`.
2. Unpack them to separate folder.
3. To load data run:
   ./opencv/build/bin/example_datasets_pd_caltech -p=/home/user/path_to_unpacked_folders/

## Enumeration Type Documentation

## § sampleType

enum cv::datasets::sampleType

`#include <opencv2/datasets/pd_inria.hpp>`

Enumerator
POS Python: cv.datasets.POS |
NEG Python: cv.datasets.NEG |