AWS Python Developer for Simple Image Processing Project
Budget: $10 – $30 USD
We're looking for a Python developer with a knack for AWS and deep learning. The task at hand? A straightforward image processing project. All you need to do is take an image from a local computer, work a little deep learning magic on it using YOLOv8 on AWS, and then return both the processed image and the associated data.
Responsibilities:
1. Set up a deep learning environment on AWS. We'll need GPU support, so you'll likely be working with EC2 or similar AWS services.
2. Write a Python script that can take an image from a local Windows PC, prepare it for processing, and upload it to an S3 bucket.
3. Set up a YOLOv8 model for custom instance segmentation. We'll need this to be efficient, so figuring out how to keep the library and dataset memory persistent will be key.
4. Create an AWS function that springs into action when an image is uploaded to the S3 bucket. This function should use the YOLOv8 model to process the image and save the segmented image and the segmentation data in the S3 bucket.
5. Develop a Python script to fetch both the processed image and the associated data from the S3 bucket and save it on the local computer.
6. Keep your code clean and well-documented. We appreciate the beauty of a well-commented code. A short report sharing what was exactly done would be great.
Requirements:
1. Solid Python programming skills.
2. Practical experience with AWS, especially S3, Lambda, and EC2 services.
3. Know your way around deep learning, preferably with YOLOv8.
4. Familiarity with GPU computing and optimization.
5. Experience with the boto3 Python library.
6. A knack for problem-solving and an eye for detail.
7. Good communication skills and the ability to work independently.
If you've worked on similar projects, we'd love to see examples in your proposal.
Responsibilities:
1. Set up a deep learning environment on AWS. We'll need GPU support, so you'll likely be working with EC2 or similar AWS services.
2. Write a Python script that can take an image from a local Windows PC, prepare it for processing, and upload it to an S3 bucket.
3. Set up a YOLOv8 model for custom instance segmentation. We'll need this to be efficient, so figuring out how to keep the library and dataset memory persistent will be key.
4. Create an AWS function that springs into action when an image is uploaded to the S3 bucket. This function should use the YOLOv8 model to process the image and save the segmented image and the segmentation data in the S3 bucket.
5. Develop a Python script to fetch both the processed image and the associated data from the S3 bucket and save it on the local computer.
6. Keep your code clean and well-documented. We appreciate the beauty of a well-commented code. A short report sharing what was exactly done would be great.
Requirements:
1. Solid Python programming skills.
2. Practical experience with AWS, especially S3, Lambda, and EC2 services.
3. Know your way around deep learning, preferably with YOLOv8.
4. Familiarity with GPU computing and optimization.
5. Experience with the boto3 Python library.
6. A knack for problem-solving and an eye for detail.
7. Good communication skills and the ability to work independently.
If you've worked on similar projects, we'd love to see examples in your proposal.