Python Jr Developer - Computer Vision Project
Budget: $2 – $8 USD
I'm seeking a junior Python developer focusing on computer vision for an upcoming project.
I have the code and steps I just need someone who knows enough Python to carry out the tasks:
Must be comfortable working with different python modules like YOLO:
Creating a script to automatically detect when a new batter comes up to the plate in a baseball game video involves several steps, including video processing, object detection, and possibly some machine learning. Here's a high-level approach to how you might achieve this:
1. **Set Up Your Environment**: Make sure you have a Python environment set up with the necessary libraries. You'll likely need OpenCV for video processing, a deep learning framework like TensorFlow or PyTorch for any machine learning models, and possibly some pre-trained models for object detection.
2. **Video Processing**: Use OpenCV to read and process the video frames.
3. **Object Detection**: Use a pre-trained model to detect players and identify when a batter is at the plate. You might use models like YOLO (You Only Look Once) or SSD (Single Shot MultiBox Detector) that can detect objects in real-time.
4. **Detect a New Batter**: Implement logic to determine when a new batter comes up. This might involve detecting changes in player positions or using additional cues like scoreboard information.
5. **Record the Time**: Each time a new batter is detected, record the current time of the video.
I have the code and steps I just need someone who knows enough Python to carry out the tasks:
Must be comfortable working with different python modules like YOLO:
Creating a script to automatically detect when a new batter comes up to the plate in a baseball game video involves several steps, including video processing, object detection, and possibly some machine learning. Here's a high-level approach to how you might achieve this:
1. **Set Up Your Environment**: Make sure you have a Python environment set up with the necessary libraries. You'll likely need OpenCV for video processing, a deep learning framework like TensorFlow or PyTorch for any machine learning models, and possibly some pre-trained models for object detection.
2. **Video Processing**: Use OpenCV to read and process the video frames.
3. **Object Detection**: Use a pre-trained model to detect players and identify when a batter is at the plate. You might use models like YOLO (You Only Look Once) or SSD (Single Shot MultiBox Detector) that can detect objects in real-time.
4. **Detect a New Batter**: Implement logic to determine when a new batter comes up. This might involve detecting changes in player positions or using additional cues like scoreboard information.
5. **Record the Time**: Each time a new batter is detected, record the current time of the video.