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Complete Guide to Creating COCO Datasets


Course Introduction :
Section Introduction
Case Study: Weed Detection
Initial setup and resources
End to end flow of the course
Course Intro Quiz
1 question

COCO Image Viewer :
Section Introduction
Overview
Initialization
Processing COCO Instances JSON
Display info, licenses, and categories
Display Image: Open and calculate resize ratio
Display Image: Polygon segmentations
Display Image: RLE segmentation concept
Display Image: RLE segmentation code
Running the notebook on the COCO Dataset
COCO Image Viewer Quiz
2 questions

Dataset Creation with GIMP :
Section Introduction
Opening, scaling, and exporting
Create first mask and export
Use layers to create second mask
Remaining images time-lapse
Mask definitions JSON
Mask definitions JSON (remaining images)
GIMP Dataset Creation Quiz
3 questions

COCO JSON Utils :
Section Introduction
Context for coco_json_utils.py
Overview
Validate and process arguments and create info
Create licenses and categories
Create images and annotations
Split multicolored mask into isolated masks
Create annotations with isolated masks
Running coco_json_utils.py
COCO JSON Utils Quiz
1 question

Foreground Cutouts with GIMP :
Section Introduction
Context for cutting out foregrounds
Foreground Select Tool (rough)
Foreground Select Tool (clean) and export
Free Select Tool with Feather Edges
Foreground Cutouts Quiz
2 questions

Image Composition :
Section Introduction
MaskJsonUtils overview, adding categories, and adding masks
Getting masks, getting super categories, and writing to json
ImageComposition overview
Validate and process arguments
Validate and process foregrounds and backgrounds
Choose random foregrounds and background
Crop background and transform foregrounds
Compose images and masks
Save images and mask definitions json
Create dataset info
Running image_composition.py and coco_json_utils.py
Image Composition Quiz
2 questions

Training Mask R-CNN :
Section Introduction
Getting started with Mask R-CNN
Preparing to train with our synthetic dataset
Training
Running inference on real test images

Course Wrap :
Overview and wrap
Last Quiz (It's easy, I promise)