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End of preview. Expand in Data Studio
IPL Player Detection Dataset — IITB PML Sem1
IPL cricket player detection dataset with cell-level team annotations and player counts. Created at IIT Bombay for the Python for Machine Learning (PML) Sem 1 project.
Dataset Overview
- 1005 images from IPL broadcast footage (800×600px)
- 8×8 grid annotation per image — each of 64 cells labeled with the IPL team present
- Player count per image (0–20)
- Train/Test split: 793 train / 212 test
- 10 IPL teams: CSK, DC, GT, KKR, LSG, MI, PBKS, RR, RCB, SRH
Use Cases
- IPL team detection from broadcast frames
- Cricket player localization and counting
- Sports image segmentation
- Multi-label classification on cricket images
- Player density estimation in cricket stadiums
Label Schema
annotations.csv columns:
| Column | Description |
|---|---|
Image File Name |
img_NNN.jpg |
Train Or Test |
Train or Test |
count |
Total player count in image (0–20) |
c01–c64 |
Team ID for each of 64 grid cells (row-major, 8 cols/row) |
Team IDs: 0=empty, 1=CSK, 2=DC, 3=GT, 4=KKR, 5=LSG, 6=MI, 7=PBKS, 8=RR, 9=RCB, 10=SRH
Folder Structure
train/ — 793 images (img_*.jpg)
test/ — 212 images (img_*.jpg)
annotations.csv — labels for all annotated images
Quick Start
import kagglehub
import pandas as pd
from pathlib import Path
from PIL import Image
# Download dataset
path = kagglehub.dataset_download("goyaljai0207/ipl-player-detection-iitb-pml")
# Load annotations
df = pd.read_csv(f"{path}/annotations.csv")
print(df.head())
# Load an image
img = Image.open(f"{path}/train/img_1.jpg")
img.show()
# Get label grid for first image
row = df.iloc[0]
grid = [[row[f'c{r*8+c+1:02d}'] for c in range(8)] for r in range(8)]
print(grid)
Also available on HuggingFace
from datasets import load_dataset
ds = load_dataset("goyaljai/IPL-Player-Detection-IITB-PML")
Team Distribution (1005 images, any-cell presence)
| Team | Images |
|---|---|
| MI | 177 |
| RCB | 153 |
| GT | 131 |
| RR | 131 |
| CSK | 130 |
| PBKS | 127 |
| LSG | 115 |
| KKR | 112 |
| DC | 110 |
| SRH | 107 |
Citation
If you use this dataset, please cite:
@dataset{ipl_player_detection_2026,
title = {IPL Player Detection Dataset},
author = {Goyal, Jai and contributors},
year = {2026},
publisher = {Kaggle},
url = {https://www.kaggle.com/datasets/goyaljai0207/ipl-player-detection-iitb-pml}
}
Keywords
IPL dataset, cricket player detection, IPL team classification, cricket image dataset, broadcast frame annotation, player count dataset, cricket computer vision, IPL 2024 dataset, sports detection dataset, IITB machine learning dataset, cricket jersey detection, multi-label cricket dataset
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