Instanse-segmentation

instanse segmentation usin mask r-cnn Sure, here is a sample README file for the provided code:

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Mask R-CNN Image Segmentation Demo

This repository contains a Jupyter Notebook file demonstrating how to use a Mask R-CNN model from TensorFlow Hub for object detection and instance segmentation. The model is capable of predicting segmentation masks for each instance of a class in an image, in addition to bounding boxes.

Installation

To run this code, you need to clone the TensorFlow Models repository and install the necessary packages. You can do this by following the instructions provided in the notebook.

Usage

1. Make sure to use a TPU runtime for this Colab due to the processing requirements of the model.
2. Load the Mask R-CNN model from TensorFlow Hub.
3. Choose a test image from the provided options.
4. Run inference on the selected image using the loaded model.
5. Visualize the results by plotting the detected objects and segmentation masks on the image.

Dependencies

• TensorFlow
• TensorFlow Hub
• Matplotlib
• NumPy
• PIL
• Six

results

References

• Mask R-CNN Paper
• TensorFlow Hub Mask R-CNN Model
• COCO Dataset

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