I updated my detection system with pruned version of “PeopleNet” model on a nano, it works well except when my IP cameras switch to night vision using infrared light, the results are really bad. Witch is normal because it was trained with RGB images at daytime.
What is the best strategy to adopt to manage both cases (day and night) ? having 2 models one for daytime and a custom one for nigh vision dealing with black and white images ?
, so I can switch between them, or having a unique model , retrained by adding night images ?
• Hardware Platform (Jetson nano / tx2 /xavier NX / xavier)
• DeepStream Version 5.0
• JetPack Version 4.4