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Precision (ROC-Recall-F1) image processing and script file

Please check the budget before contacting me.

I have a fully trained convolution neural network model (coded in tensorflow) designed and trained for capturing the oil spilled areas in ocean images. It can semantically segment the input images into two categories: background and the oil.

However, I need to extend the code and retrain it with a new dataset, so I can measure the segmentation accuracy of the input images as threshold the data and calculate the accuracy of detection. So the hard part was finished

Basically, the project has three main parts.

1) Calculate the accuracy of the segmentation using a suitable metric (F1-Recall-Precision) .

2) Visualize the accuracies and precision with a graph/plot."

3) Create one line command to install the needed library like exe file to install (pip – opencv – numpy – pillow – scipy – matblotlib – tensorflow – and any other needed function or library ) to avoid any problems with any normal user.

b. Explain what have been done in simple word file

Skills: Image Processing, Machine Learning, Python

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About the Employer:
( 2 reviews ) Cairo, Korea, Republic of

Project ID: #17264538

1 freelancer is bidding on average $30 for this job


Completed a very similar project for final year machine learning assignment. Well versed woth scikit,numpy,tensorflow and pytorch

$30 USD in 5 days
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