Python cv2.resizeWindow方法代码示例

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def createFigureAndSlider(name, state_dim):
    """
    Creating a window for the latent space visualization, an another for the slider to control it
    :param name: name of model (str)
    :param state_dim: (int)
    :return:
    """
    # opencv gui setup
    cv2.namedWindow(name, cv2.WINDOW_NORMAL)
    cv2.resizeWindow(name, 500, 500)
    cv2.namedWindow('slider for ' + name)
    # add a slider for each component of the latent space
    for i in range(state_dim):
        # the sliders MUST be between 0 and max, so we placed max at 100, and start at 50
        # So that when we substract 50 and divide 10 we get [-5,5] for each component
        cv2.createTrackbar(str(i), 'slider for ' + name, 50, 100, (lambda a: None)) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def demo():
    import os
    from vizer.draw import draw_boxes

    yolo = YOLOv3("cfg/yolo_v3.cfg", "weight/yolov3.weights", "cfg/coco.names")
    print("yolo.size =", yolo.size)
    root = "./demo"
    resdir = os.path.join(root, "results")
    os.makedirs(resdir, exist_ok=True)
    files = [os.path.join(root, file) for file in os.listdir(root) if file.endswith('.jpg')]
    files.sort()
    for filename in files:
        img = cv2.imread(filename)
        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        bbox, cls_conf, cls_ids = yolo(img)

        if bbox is not None:
            img = draw_boxes(img, bbox, cls_ids, cls_conf, class_name_map=yolo.class_names)
        # save results
        cv2.imwrite(os.path.join(resdir, os.path.basename(filename)), img[:, :, (2, 1, 0)])
        # imshow
        # cv2.namedWindow("yolo", cv2.WINDOW_NORMAL)
        # cv2.resizeWindow("yolo", 600,600)
        # cv2.imshow("yolo",res[:,:,(2,1,0)])
        # cv2.waitKey(0) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def train_generator(self, image_generator, mask_generator):
        # cv2.namedWindow('show', 0)
        # cv2.resizeWindow('show', 1280, 640)
        while True:
            image = next(image_generator)
            mask = next(mask_generator)
            label = self.make_regressor_label(mask).astype(np.float32)
            # print (image.dtype, label.dtype)
            # print (image.shape, label.shape)
            # exit()
            # cv2.imshow('show', image[0].astype(np.uint8))
            # cv2.imshow('label', label[0].astype(np.uint8))
            # mask = self.select_labels(mask)
            # print (image.shape)
            # print (mask.shape)
            # image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
            # mask = (mask.astype(np.float32)*255/33).astype(np.uint8)
            # mask_color = cv2.applyColorMap(mask, cv2.COLORMAP_JET)
            # print (mask_color.shape)
            # show = cv2.addWeighted(image, 0.5, mask_color, 0.5, 0.0)
            # cv2.imshow("show", show)
            # key = cv2.waitKey()
            # if key == 27:
            #     exit()
            yield (image, label) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def cv2_show_image(window_name, image,
                   size_wh=None, location_xy=None):
    """Helper function for specifying window size and location when
    displaying images with cv2.

    Args:
        window_name: str window name
        image: ndarray image to display
        size_wh: window size (w, h)
        location_xy: window location (x, y)
    """

    if size_wh is not None:
        cv2.namedWindow(window_name,
                        cv2.WINDOW_KEEPRATIO | cv2.WINDOW_GUI_NORMAL)
        cv2.resizeWindow(window_name, *size_wh)
    else:
        cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)

    if location_xy is not None:
        cv2.moveWindow(window_name, *location_xy)

    cv2.imshow(window_name, image) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def __init__(self, cfg, args, video_path):
        self.cfg = cfg
        self.args = args
        self.video_path = video_path
        self.logger = get_logger("root")

        use_cuda = args.use_cuda and torch.cuda.is_available()
        if not use_cuda:
            warnings.warn("Running in cpu mode which maybe very slow!", UserWarning)

        if args.display:
            cv2.namedWindow("test", cv2.WINDOW_NORMAL)
            cv2.resizeWindow("test", args.display_width, args.display_height)

        if args.cam != -1:
            print("Using webcam " + str(args.cam))
            self.vdo = cv2.VideoCapture(args.cam)
        else:
            self.vdo = cv2.VideoCapture()
        self.detector = build_detector(cfg, use_cuda=use_cuda)
        self.deepsort = build_tracker(cfg, use_cuda=use_cuda)
        self.class_names = self.detector.class_names 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def show_pic(img, bboxes=None, name='pic'):
    '''
    输入:
        img:图像array
        bboxes:图像的所有boudning box list, 格式为[[x_min, y_min, x_max, y_max]....]
        names:每个box对应的名称
    '''
    show_img = img.copy()
    if not isinstance(bboxes, np.ndarray):
        bboxes = np.array(bboxes)
    for point in bboxes.astype(np.int):
        cv2.line(show_img, tuple(point[0]), tuple(point[1]), (255, 0, 0), 2)
        cv2.line(show_img, tuple(point[1]), tuple(point[2]), (255, 0, 0), 2)
        cv2.line(show_img, tuple(point[2]), tuple(point[3]), (255, 0, 0), 2)
        cv2.line(show_img, tuple(point[3]), tuple(point[0]), (255, 0, 0), 2)
    # cv2.namedWindow(name, 0)  # 1表示原图
    # cv2.moveWindow(name, 0, 0)
    # cv2.resizeWindow(name, 1200, 800)  # 可视化的图片大小
    cv2.imshow(name, show_img)


# 图像均为cv2读取 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def draw_box(img, joints):
    overlay = img[0].copy()
    for i in range(1, 16):
        if joints[i]:
            for j in range(len(joints[i][0])):
                box = joints[i][0][j]
                tl_x, tl_y, br_x, br_y = int(box[2] - 0.5 * box[4]), int(box[3] - 0.5 * box[5]), \
                                         int(box[2] + 0.5 * box[4]), int(box[3] + 0.5 * box[5])
                cv2.rectangle(overlay, (tl_x, tl_y), (br_x, br_y), colors[i-1], -1)

    img_transparent = cv2.addWeighted(overlay, alpha, img[0], 1 - alpha, 0)[:, :, ::-1]
    img_transparent[:, ::cfg.CELL_SIZE, :] = np.array([1., 1, 1])
    img_transparent[::cfg.CELL_SIZE, :, :] = np.array([1., 1, 1])
    cv2.namedWindow('box', cv2.WINDOW_NORMAL)
    cv2.resizeWindow('box', 600, 600)
    cv2.imshow('box', img_transparent)
    key = cv2.waitKey(0)
    if key == ord('s'):
        cv2.imwrite('box.png', img_transparent * 255) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def draw_limb(img, persons):
    overlay = img[0].copy()
    for p in persons:
        for j in range(1, 16):
            if p[j][0] == -1 or p[j][1] == -1:
                continue
            cv2.circle(overlay, (int(p[j][0]), int(p[j][1])), 3, colors[j-1],
                       -1, cv2.LINE_AA)

    for p in persons:
        for j in range(14):
            j1, j2 = p[limbs1[j]], p[limbs2[j]]
            if (j1 == -1).any() or (j2 == -1).any():
                continue
            cv2.line(overlay, (int(j1[0]), int(j1[1])), (int(j2[0]), int(j2[1])),
                     colors[j], 2, cv2.LINE_AA)
    img_dst = cv2.addWeighted(overlay, alpha, img[0], 1-alpha, 0)[:, :, ::-1]
    cv2.namedWindow('persons', cv2.WINDOW_NORMAL)
    cv2.resizeWindow('persons', 600, 600)
    cv2.imshow('persons', img_dst)
    key = cv2.waitKey(0)
    if key == ord('s'):
        cv2.imwrite('persons.png', img_dst * 255) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def showimg(img):
        cv2.namedWindow("contours", 0);
        cv2.resizeWindow("contours", 1280, 720);
        cv2.imshow("contours", img)
        cv2.waitKey()

#psm model:
#  0    Orientation and script detection (OSD) only.
#  1    Automatic page segmentation with OSD.
#  2    Automatic page segmentation, but no OSD, or OCR.
#  3    Fully automatic page segmentation, but no OSD. (Default)
#  4    Assume a single column of text of variable sizes.
#  5    Assume a single uniform block of vertically aligned text.
#  6    Assume a single uniform block of text.
#  7    Treat the image as a single text line.
#  8    Treat the image as a single word.
#  9    Treat the image as a single word in a circle.
#  10    Treat the image as a single character.
#  11    Sparse text. Find as much text as possible in no particular order.
#  12    Sparse text with OSD.
#  13    Raw line. Treat the image as a single text line,
# 			bypassing hacks that are Tesseract-specific 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def analyze_picture(model_emotion, model_gender, path, window_size, window_name='static'):
    cv2.namedWindow(window_name, WINDOW_NORMAL)
    cv2.namedWindow(window_name, WINDOW_NORMAL)
    if window_size:
        width, height = window_size
        cv2.resizeWindow(window_name, width, height)

    image = cv2.imread(path, 1)
    for normalized_face, (x, y, w, h) in find_faces(image):
        emotion_prediction = model_emotion.predict(normalized_face)
        gender_prediction = model_gender.predict(normalized_face)
        if (gender_prediction[0] == 0):
            cv2.rectangle(image, (x,y), (x+w, y+h), (0,0,255), 2)
        else:
            cv2.rectangle(image, (x,y), (x+w, y+h), (255,0,0), 2)
        cv2.putText(image, emotions[emotion_prediction[0]], (x,y-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,255,255), 2)
    cv2.imshow(window_name, image)
    key = cv2.waitKey(0)
    if key == ESC:
        cv2.destroyWindow(window_name) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def show_webcam_and_run(model, emoticons, window_size=None, window_name='webcam', update_time=10):
    """
    Shows webcam image, detects faces and its emotions in real time and draw emoticons over those faces.
    :param model: Learnt emotion detection model.
    :param emoticons: List of emotions images.
    :param window_size: Size of webcam image window.
    :param window_name: Name of webcam image window.
    :param update_time: Image update time interval.
    """
    cv2.namedWindow(window_name, WINDOW_NORMAL)
    if window_size:
        width, height = window_size
        cv2.resizeWindow(window_name, width, height)

    vc = cv2.VideoCapture(0)
    if vc.isOpened():
        read_value, webcam_image = vc.read()
    else:
        print("webcam not found")
        return

    while read_value:
        for normalized_face, (x, y, w, h) in find_faces(webcam_image):
            prediction = model.predict(normalized_face)  # do prediction
            if cv2.__version__ != '3.1.0':
                prediction = prediction[0]

            image_to_draw = emoticons[prediction]
            draw_with_alpha(webcam_image, image_to_draw, (x, y, w, h))

        cv2.imshow(window_name, webcam_image)
        read_value, webcam_image = vc.read()
        key = cv2.waitKey(update_time)

        if key == 27:  # exit on ESC
            break

    cv2.destroyWindow(window_name) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def train_visualization_seg(self, model, epoch, path):
        # image_name_list = sorted(glob(os.path.join(self.flag.data_path,'val/IMAGE/*/frankfurt_000000_014480_leftImg8bit.png')))
        # print (image_name_list)

        image_name = path #'./result/frankfurt_000000_014480_leftImg8bit.png'
        image_height = self.flag.image_height
        image_width = self.flag.image_width
        
        imgInput = cv2.imread(image_name, self.flag.color_mode)
        imgInput = cv2.cvtColor(imgInput, cv2.COLOR_BGR2RGB)
        output_path = self.flag.output_dir
        input_data = imgInput.reshape((1,image_height,image_width,self.flag.color_mode*2+1))

        t_start = cv2.getTickCount()
        result = model.predict(input_data, 1)
        t_total = (cv2.getTickCount() - t_start) / cv2.getTickFrequency() * 1000
        print ("[*] Predict Time: %.3f ms"%t_total)
        
        imgMask = (result[0]*255).astype(np.uint8)
        imgShow = cv2.cvtColor(imgInput, cv2.COLOR_RGB2BGR).copy()
        #cv2.cvtColor(imgInput, cv2.COLOR_GRAY2BGR)
        # imgMaskColor = cv2.applyColorMap(imgMask, cv2.COLORMAP_JET)
        imgMaskColor = imgMask
        imgShow = cv2.addWeighted(imgShow, 0.5, imgMaskColor, 0.6, 0.0)
        output_path = os.path.join(self.flag.output_dir, '%04d_'%epoch+os.path.basename(image_name))
        mask_path = os.path.join(self.flag.output_dir, 'mask_%04d_'%epoch+os.path.basename(image_name))
        cv2.imwrite(output_path, imgShow)
        cv2.imwrite(mask_path, imgMaskColor)
        # print "SAVE:[%s]"%output_path
        # cv2.imwrite(os.path.join(output_path, 'img%04d.png'%epoch), imgShow)
        # cv2.namedWindow("show", 0)
        # cv2.resizeWindow("show", 800, 800)
        # cv2.imshow("show", imgShow)
        # cv2.waitKey(1) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def main():
    image = data.astronaut()
    image = ia.imresize_single_image(image, (64, 64))
    print("image shape:", image.shape)
    print("Press any key or wait %d ms to proceed to the next image." % (TIME_PER_STEP,))

    k = [
        1,
        2,
        4,
        8,
        16,
        (8, 8),
        (1, 8),
        ((1, 1), (8, 8)),
        ((1, 16), (1, 16)),
        ((1, 16), 1)
    ]

    cv2.namedWindow("aug", cv2.WINDOW_NORMAL)
    cv2.resizeWindow("aug", 64*NB_AUGS_PER_IMAGE, 64)

    for ki in k:
        aug = iaa.AverageBlur(k=ki)
        img_aug = [aug.augment_image(image) for _ in range(NB_AUGS_PER_IMAGE)]
        img_aug = np.hstack(img_aug)
        print("dtype", img_aug.dtype, "averages", np.average(img_aug, axis=tuple(range(0, img_aug.ndim-1))))

        title = "k=%s" % (str(ki),)
        img_aug = ia.draw_text(img_aug, x=5, y=5, text=title)

        cv2.imshow("aug", img_aug[..., ::-1])  # here with rgb2bgr
        cv2.waitKey(TIME_PER_STEP) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def main():
    image = data.astronaut()
    image = ia.imresize_single_image(image, (128, 128))
    print("image shape:", image.shape)
    print("Press any key or wait %d ms to proceed to the next image." % (TIME_PER_STEP,))

    configs = [
        (1, 75, 75),
        (3, 75, 75),
        (5, 75, 75),
        (10, 75, 75),
        (10, 25, 25),
        (10, 250, 150),
        (15, 75, 75),
        (15, 150, 150),
        (15, 250, 150),
        (20, 75, 75),
        (40, 150, 150),
        ((1, 5), 75, 75),
        (5, (10, 250), 75),
        (5, 75, (10, 250)),
        (5, (10, 250), (10, 250)),
        (10, (10, 250), (10, 250)),
    ]

    cv2.namedWindow("aug", cv2.WINDOW_NORMAL)
    cv2.resizeWindow("aug", 128*NB_AUGS_PER_IMAGE, 128)

    for (d, sigma_color, sigma_space) in configs:
        aug = iaa.BilateralBlur(d=d, sigma_color=sigma_color, sigma_space=sigma_space)

        img_aug = [aug.augment_image(image) for _ in range(NB_AUGS_PER_IMAGE)]
        img_aug = np.hstack(img_aug)
        print("dtype", img_aug.dtype, "averages", np.average(img_aug, axis=tuple(range(0, img_aug.ndim-1))))

        title = "d=%s, sc=%s, ss=%s" % (str(d), str(sigma_color), str(sigma_space))
        img_aug = ia.draw_text(img_aug, x=5, y=5, text=title)

        cv2.imshow("aug", img_aug[..., ::-1]) # here with rgb2bgr
        cv2.waitKey(TIME_PER_STEP) 

# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import resizeWindow [as 别名]
def main():
    image = data.astronaut()
    image = ia.imresize_single_image(image, (64, 64))
    print("image shape:", image.shape)
    print("Press any key or wait %d ms to proceed to the next image." % (TIME_PER_STEP,))

    k = [
        1,
        3,
        5,
        7,
        (3, 3),
        (1, 11)
    ]

    cv2.namedWindow("aug", cv2.WINDOW_NORMAL)
    cv2.resizeWindow("aug", 64*NB_AUGS_PER_IMAGE, 64)

    for ki in k:
        aug = iaa.MedianBlur(k=ki)
        img_aug = [aug.augment_image(image) for _ in range(NB_AUGS_PER_IMAGE)]
        img_aug = np.hstack(img_aug)
        print("dtype", img_aug.dtype, "averages", np.average(img_aug, axis=tuple(range(0, img_aug.ndim-1))))

        title = "k=%s" % (str(ki),)
        img_aug = ia.draw_text(img_aug, x=5, y=5, text=title)

        cv2.imshow("aug", img_aug[..., ::-1]) # here with rgb2bgr
        cv2.waitKey(TIME_PER_STEP)