Deep-Transit detects transits using a deep learning based 2D object detection algorithm. The code determines the light curve and outputs the transiting candidates' bounding boxes and confidence scores. It has been trained for Kepler and TESS data, and can be extended to other photometric surveys and even ground-based observations. Deep-Transit also provides an interface for training new datasets.