Personal Accomplishments
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- Dash Cam Bringup:
- Added a dip switch and software script to allow users to opt in or opt out of the ALPR mode
- Refactored GPS code to make it nonblocking when GPS signal is not detected and debugged GPS connection issues on power on
- Implemented sync match image chunk upload and experimented with async match upload using thread
- Both HTTP GET and HTTP POST use the same I2C address, so I have to implement a locking mechanism
- This results in a traffic jam that we think is not worth for implementing async chunk image upload
- So we decided to stop further inferencing when we are uploading a match image
- Dash Cam Testing:
- Added an LED to indicate the stage of the dash cam for easier road testing, LED is ON during setup, LED flashes slowly during recording, and LED flashes faster during inference
- Wrote a pure recording script to record real-road footage for future demos
- Worked with Christine and Andy to conduct a 30 minute road test under rainy setting
- Dash Cam Verification:
- Verified that the dash cam records continuously in 1-minute clips for 10 minutes in a stationary setup
- Verified that the dash cam records continuous footage under five separate real-driving tests of at least five minutes each
- ALPR Verification:
- Benchmarked the YOLOv11n model using a curated set of 386 real-world images sourced from the Kaggle-based dataset, achieving 90.4% mAP50
- Benchmarked the PaddleOCRv3rec component on the scraped dataset from platesmania.com, which includes 4,000 cropped synthetic U.S. license plate images and 1,000 cropped real-world images, achieving 93% accuracy
- Benchmarked the end-to-end ALPR pipeline by passing 5,000 full-frame, real-world images from platesmania.com through the system, achieving 81% accuracy
- Dash Cam Bringup:
Progress
My progress is on schedule.
Schedule
- Road tests
- Dash cam pipeline fixes (API key integration, etc.)
- Scripts for demo purposes