Python Deep Learning Projects

Preparing the data

Let us now define a data_list() function that will automate the process of loading an image and its segmentation array into memory and resize them to the shape of 360*480 using OpenCV. This function returns two lists containing images and segmentation array:

def data_list(imgIds, count = 12127, ratio = 0.2):    """Function to load image and its target into memory."""     img_lst = []    lab_lst = []    for x in tqdm(imgIds[0:count]):        # load image details        img = coco.loadImgs(x)[0]                # read image        I = io.imread('images/train2014/'+img['file_name'])        if len(I.shape)<3:            continue                # load annotation information        annIds = coco.getAnnIds(imgIds=img['id'], catIds=catIds, iscrowd=None)                # load annotation        anns = coco.loadAnns(annIds)                # prepare mask ...