aman-17 / tshirt-segmentation-using-mrcnn

Tshirt instance segmentation using MRCNN.

Mask R-CNN for Object Detection and Segmentation

This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone.

Requirements

Python 3.6.9 and other common packages listed in requirements.txt. Do not install different versions of tensorflow and keras.

Installation

1. Clone this repository
2. Install dependencies

   pip3 install -r requirements.txt

3. Run train.py file

   python3 train.py

Getting Started

• Download the tshirt dataset .zip file from here and extract it. Annotations file is inside the folder with name annotations_train.json

• (model.py, utils.py, config.py): These files contain the main Mask RCNN implementation.

• (train.py): To train the model use this file. Use the same path for dataset_train and dataset_val in train.py as we are using 10% of images from training dataset for measuring validation loss.

• (train_mask_rcnn_demo.py) is used give no. of classes, batch size, steps_per_epoch, epochs, gpu_count, images_per_gpu. Change them as per your convinence wrt your GPU. You can change epochs in train_head and train_all_layers functions in line267 and line274 respectively.

• For Downloading the dataset

pip install gdown gdown --fuzzy https://drive.google.com/file/d/1aGLstfgFbBMZih_OaBaiuB40ZI8DxLpK/view?usp=sharing