#In imageAI we have RetinaNet, YOLOv3 and TinyYOLOv3 for objet detection from imageai.Detection import ObjectDetection # import the ImageAI object detection class import os working_path = os.getcwd() res = ObjectDetection() #create an object of the ObjectDetection class res.setModelTypeAsYOLOv3() # https://github.com/OlafenwaMoses/ImageAI/releases/download/1.0/yolo.h5 res.setModulePath(os.path.join( working_path, "yolo.h5")) #set the model path to the YOLOv3 model file res.loadModel() detection = res.detectObjectsFromImage( input_image=os.path.join(working_path, image_1.jpg), output_image_path=os.path.join(working_path, image_2.jpg), minimum_percentage_probability=30) #Display for obj in detection: print(obj["name"], " : ", obj["percentage_probability"], " : ", obj["box_points"]) # we can also use RetinaNet which is appropriate for high-performance and high-accuracy tasks # https://github.com/OlafenwaMoses/ImageAI/releases/download/1.0/resnet50_coco_best_v2.0.1.h5 # res = ObjectDetection() # res.setModelTypeAsRetinaNet() # res.setModelPath( os.path.join(execution_path , "resnet50_coco_best_v2.0.1.h5")) # res.loadModel()