[업데이트 2019.02.14 17:09] 먼저 Dockerfile이 위치한 디렉토리로 이동합니다. 만약 Docker Hub에 이미지를 올릴려면, 계정 생성 및 저장소를 생성해야합니다. (https://hub.docker.com) Docker 이미지 이름의 컨벤션은 아래와 같습니다. /: ex) aibakevision/web-ui:0.0.1 1. 컨테이너 빌드 빌드시 빌드 이미지 이름을 파라메터 -t와 함께 넘겨주며, 빌드 디렉토리로 . 를 줍니다. 현재 디렉토리를 기준으로 빌드를 수행합니다. docker build -t aibakevision/web-ui:0.0.1 . ubuntu@server:~/projects/crested-gecko/web-ui$ docker build -t aibakevision..
[업데이트 2019.05.08 16:21] This is a web-based object detection service. It provides detecting various type of objects. The state-of-the-art deep learning computer vision technology, “YOLO” based on Darknet is used. The Darknet is CUDA and C++ based deep learning framework. The pre-trained YOLOv3-608 model which is trained by the COCO dataset is deployed. I created new dataset for crested gecko det..
The project “Black Pebble” is an AI based IoT service for monitoring the temperature and humidity in the reptile vivarium. It provides the real-time monitoring application and the users can remotely check the temperature and humidity in their vivariums. The main feature of this service is AI based monitoring. It provides the prediction service of the temperature and humidity through time-series ..
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