[Question] Need arrow dataset images for shape detection project
📰 Reddit r/learnprogramming
Learn how to generate synthetic arrow images and train a CNN model for shape detection
Action Steps
- Generate synthetic arrow images using Python libraries like OpenCV or Pillow
- Create a custom CNN model using TensorFlow or PyTorch to classify arrow shapes
- Train the model on the generated dataset and evaluate its performance
- Use data augmentation techniques to increase the diversity of the arrow images
- Test the model on real-world images to assess its accuracy and robustness
Who Needs to Know This
Machine learning engineers and data scientists working on computer vision projects can benefit from this knowledge to improve their shape detection models
Key Insight
💡 Generating synthetic images can be a viable alternative to finding existing datasets for specific tasks like arrow shape detection
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🚀 Need arrow dataset images for shape detection? Generate synthetic images using Python and train a custom CNN model! 🤖
Key Takeaways
Learn how to generate synthetic arrow images and train a CNN model for shape detection
Full Article
Hi everyone, I’m working on a shape detection project where the user draws on a whiteboard/canvas, and the system converts the drawing into a detected shape. The project supports multiple shapes, including different types of arrows. My main problem is the arrow dataset. I couldn’t find a good dataset containing many arrow variations, so I tried generating synthetic images using a Python script and trained a custom CNN model on them, but the
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