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Prerequisites & Installation

  • Prerequisites
  • Installation

Tutorials

  • Videos on YouTube
  • UI Documentation
  • What is Supervisely Agent
  • Exam Reports Explained

API

  • Python SDK API Reference
  • Public REST API

SDK Basics with IPython Notebooks

  • SDK Basics with IPython Notebooks
    • 1. Project Structure
    • 2. Data Management
    • 3. Data Augmentations
    • 4. NN: Deploy and Inference on Supervisely via API
    • 5. NN: Automate training and inference via API
    • 6. Inference Modes: Full Image / Sliding Window / ROI / Bboxes
    • 7. Data Manipulation via API: Copy / Move / Delete
    • 8. Users and Labeling Jobs API
    • 9.1. Custom NN Detection and Segmentation Pipeline
      • 1. Imports
      • 2. Initialize API Access with your Credentials
      • 3. Initialize the API Access Object
      • 4. Script Parameters
      • 5. Verify Parameters
      • 6. Deploy both Detection and Segmentataion Models (if not deployed before)
      • 7. Get Models Ouptut Classes (+ check that models are deployed correctly)
      • 8. Apply Detection Model (sliding window)
      • 9. Apply Segmentation Model (sliding window)
      • 10. Postprocessing Step: Keep only Ties that are on the Cats
    • 9.2. Custom NN Multi GPU Detection and Segmentation Pipeline
    • 10. Upload Images via API
    • 11. Custom Data Pipeline
    • 12. Filter and Combine Images
    • 13. NN Inference from Sources
    • 14. How to Work with NN Pixelwise Probabilities
    • Additional Examples in our GitHub

Applications Development (In Progress)

  • Getting Started
  • First Application (Coming soon)

Develop Plugins (Deprecated)

  • Custom Plugin Basics
  • Custom NN Plugin Basics
  • How to Debug Custom NN Plugin
  • Different Ways How to Deploy NN with Supervisely

Source Code

  • Supervisely GitHub
  • Supervisely Ecosystem

Troubleshooting

  • Install issues
Supervisely SDK for Python
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  • Python SDK Tutorial β„–9.1: Custom NN Detection and Segmentation Pipeline
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Python SDK Tutorial β„–9.1: Custom NN Detection and Segmentation PipelineΒΆ

  • 1. Imports
  • 2. Initialize API Access with your Credentials
  • 3. Initialize the API Access Object
  • 4. Script Parameters
  • 5. Verify Parameters
  • 6. Deploy both Detection and Segmentataion Models (if not deployed before)
  • 7. Get Models Ouptut Classes (+ check that models are deployed correctly)
  • 8. Apply Detection Model (sliding window)
  • 9. Apply Segmentation Model (sliding window)
  • 10. Postprocessing Step: Keep only Ties that are on the Cats
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