Is it free to convert Kaggle Wheat CSV to meituan/yolov6?
Yes! It is free to convert Kaggle Wheat CSV data into the meituan/yolov6 format on the Roboflow platform.
Convert annotation formats
How To Convert Kaggle Wheat CSV to meituan/yolov6
In this guide, we show you how to convert data between the Wheat and MT-YOLOv6 formats for free. You can use your converted data to train MT-YOLOv6 models and other models that support the MT-YOLOv6 format.
Kaggle Wheat CSVtomeituan/yolov6
Kaggle Wheat CSV
Custom format used in a specific Kaggle object detection competition.
Below, learn the structure of Kaggle Wheat CSV.
kaggle.wheat.csv
image_id,width,height,bbox,source
b6ab77fd7,1024,1024,"[834.0, 222.0, 56.0, 36.0]",usask_1
b6ab77fd7,1024,1024,"[226.0, 548.0, 130.0, 58.0]",usask_1
b6ab77fd7,1024,1024,"[377.0, 504.0, 74.0, 160.0]",usask_1
b6ab77fd7,1024,1024,"[834.0, 95.0, 109.0, 107.0]",usask_1
b6ab77fd7,1024,1024,"[26.0, 144.0, 124.0, 117.0]",usask_1
b6ab77fd7,1024,1024,"[569.0, 382.0, 119.0, 111.0]",usask_1
b6ab77fd7,1024,1024,"[52.0, 602.0, 82.0, 45.0]",usask_1
b6ab77fd7,1024,1024,"[627.0, 302.0, 122.0, 75.0]",usask_1
b6ab77fd7,1024,1024,"[412.0, 367.0, 68.0, 82.0]",usask_1meituan/yolov6
MT-YOLOv6 uses a modified version of YOLO Darknet annotations.
Below, learn the structure of meituan/yolov6.
The annotation format is the same as YOLOv5 but with changes to the YAML file. Each image has one txt file with a single line for each bounding box. The format of each row is
class_id center_x center_y width height
where fields are space delimited, and the coordinates are normalized from zero to one.
Note: To convert to normalized xywh from pixel values, divide x (and width) by the image's width and divide y (and height) by the image's height.
001.txt
1 0.617 0.3594420600858369 0.114 0.17381974248927037
1 0.094 0.38626609442060084 0.156 0.23605150214592274
1 0.295 0.3959227467811159 0.13 0.19527896995708155
1 0.785 0.398068669527897 0.07 0.14377682403433475
1 0.886 0.40879828326180256 0.124 0.18240343347639484
1 0.723 0.398068669527897 0.102 0.1609442060085837
1 0.541 0.35085836909871243 0.094 0.16952789699570817
1 0.428 0.4334763948497854 0.068 0.1072961373390558
1 0.375 0.40236051502145925 0.054 0.1351931330472103
1 0.976 0.3927038626609442 0.044 0.17167381974248927The `data.yaml` file contains configuration values used by the model to locate images and map class names to class_id's.
data.yaml
train: ./images/train
val: ./images/valid
test: ./images/test
nc: 3
names: ['head', 'helmet', 'person']
Step 1: Create a free Roboflow public workspace
Roboflow is a universal conversion tool for computer vision annotation formats. The Public plan is the best way for those exploring personal projects, class assignments, and other experiments to try Roboflow. To convert your dataset, start by creating a free workspace on the Public plan.
Step 2: Upload your data into Roboflow
Once your account has been created, click Create New Project.
Upload your data to Roboflow by dragging and dropping your Kaggle Wheat CSV images and annotations into the upload space.
Step 3: Generate Dataset Version
Next, click "Generate New Version" to generate a new version of your dataset:
You can then apply any preprocessing or augmentation steps to your dataset:
Step 4: Export Dataset Version
After generating, you will be prompted to Export your dataset. You can choose to receive your dataset as a .zip file or a curl download link. Choose meituan/yolov6 when asked in what format you want to export your data. You will see a dropdown with various options like this:
Congratulations, you have successfully converted your dataset from Kaggle Wheat CSV format to meituan/yolov6 format!
Video Tutorial
Convert Computer Vision Annotation Formats Tutorial
Want to dive deeper into converting annotation formats with Roboflow? In the tutorial below, we explore how to convert your data in the Roboflow dashboard. We also discuss rejecting annotations and train-test-validation splits.
Frequently Asked Questions
Yes! It is free to convert Kaggle Wheat CSV data into the meituan/yolov6 format on the Roboflow platform.
If you have between a few and a few thousand images, converting data between these formats will be quick. But, the time it takes to convert between data formats increases with the more images you have.
Convert Kaggle Wheat CSV to other formats
- COCO JSON
- COCO Run-Length Encoding (RLE)
- CreateML JSON
- Florence-2
- Google Cloud AutoML Vision CSV
- Multiclass Classification CSV
- OpenAI CLIP Classification
- OpenAI GPT-4o Object Detection JSONL
- PaliGemma JSONL
- Pascal VOC XML
- RetinaNet Keras CSV
- Sagemaker GroundTruth Manifest
- Scaled-YOLOv4 TXT
- Tensorflow Object Detection CSV
- Tensorflow TFRecord
- YOLO Darknet TXT
- YOLO Keras TXT
- YOLOv10 PyTorch TXT
- YOLOv11 PyTorch TXT
- YOLOv4 PyTorch TXT
- YOLOv5 Oriented Bounding Boxes
- YOLOv5 PyTorch TXT
- YOLOv7 PyTorch TXT
- YOLOv8 Oriented Bounding Boxes
- YOLOv8 PyTorch TXT
- YOLOv9 PyTorch TXT
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