Пример #1
0
def red_detect(frame):  # オレンジ色を検出し、画像加工を施す。
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    lower = (0, 230, 150)
    upper = (30, 255, 255)
    red = cv2.inRange(hsv, lower, upper)
    kernal = np.ones((5, 5), "uint8")
    red = cv2.dilate(red, kernal)
    res = cv2.bitwise_and(frame, frame, mask=red)
    (ret, contours, hierarchy) = cv2.findContours(
        red, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    x = 0
    y = 0
    w = 0
    h = 0
    for pic, contour in enumerate(contours):
        area = cv2.contourArea(contour)
        if (area > 100):
            x, y, w, h = cv2.boundingRect(contour)
            frame = cv2.rectangle(
                frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
            cv2.putText(frame, "RED color", (x, y),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255))
            cv2.drawMarker(frame, (480, 350), (255, 255, 0),
                           markerType=cv2.MARKER_SQUARE, markerSize=5, thickness=10)
            cv2.drawMarker(frame, ((x + w//2), (y + h//2)), (255, 255, 0),
                           markerType=cv2.MARKER_SQUARE, markerSize=5, thickness=10)
            cv2.arrowedLine(frame, (480, 350),
                            ((x + w//2), (y + h//2)), (255, 0, 0), 5)
            cv2.rectangle(frame, (330, 200), (630, 500), (0, 255, 0), 1)
    return frame, x, y, w, h  # 動画データとピクセル(x,y,z,h)を返す
Пример #2
0
def main(anchorFrame,
         targetFrame,
         outfile="OUTPUT",
         saveOutput=False,
         blockSize=8):
    """
    
    :param anchor: file path of I-Frame or I-Frame
    :param target: file path of Current Frame or Current Frame
    :return: image with vectors
    """
    editedFrame = copy.copy(targetFrame)
    anchorFrame, targetFrame = preprocess(
        anchorFrame, targetFrame,
        blockSize)  #processes frame or filepath to frame

    hSegments, wSegments = segmentImage(anchorFrame, blockSize)
    vectors = blockSearchBody(anchorFrame, targetFrame, blockSize)

    bcount = 0
    for y in range(0, int(hSegments * blockSize), blockSize):
        for x in range(0, int(wSegments * blockSize), blockSize):
            if (x, y) != vectors[bcount]:
                #print((x,y))
                #print(vectors[bcount])
                p = vectors[bcount]
                cv2.arrowedLine(
                    editedFrame,
                    (p[0] + int(blockSize / 2), p[1] + int(blockSize / 2)),
                    (x + int(blockSize / 2), y + int(blockSize / 2)),
                    (0, 255, 0), 1)
            bcount = bcount + 1

    return editedFrame
def click_event(event, x, y, flags, param):
    if event == cv2.EVENT_LBUTTONDOWN:
        cv2.circle(img, (x,y), 3, (0,0,255), -1)  # Produce the circle at the clicked points 

        point_coords.append((x,y))

        if len(point_coords)>=2:
            # Producing the line from Point1 to Point2
            cv2.arrowedLine(img, (point_coords[-2]), (point_coords[-1]), (0,255,0), 2)

        cv2.imshow('Window1', img)
Пример #4
0
def draw_path(image, route, index, stations):
    paths_color = [
        (10, 164, 62),  # green
        (235, 23, 23),  # red
        (8, 117, 191),  # blue
        (254, 205, 0)  # yellow
    ]
    route_color = paths_color[index]

    if len(route['route']) > 1:
        for point_index, station_index in enumerate(route['route'][:-1]):
            station = stations[station_index]
            next_station_index = route['route'][point_index + 1]
            next_station = stations[next_station_index]
            pt1 = (station['centroid'][0], station['centroid'][1])
            pt2 = (next_station['centroid'][0], next_station['centroid'][1])
            cv2.arrowedLine(image, pt1, pt2, route_color, 3)
Пример #5
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import numpy as np
from cv2 import cv2

# img = cv2.imread("Screenshot (123).png", 1)

img = np.zeros([512, 512, 3], np.uint8)

img = cv2.line(img, (350,350), (700, 350), (90, 15, 50), 10)
img = cv2.arrowedLine(img, (700, 350), (1050, 350), (50,15,90), 10)

img = cv2.rectangle(img, (350, 355), (700, 700), (150,0,135), -1)

img = cv2.circle(img, (500, 500), 100, (150, 0, 135), -1)
font = cv2.FONT_HERSHEY_SIMPLEX
img = cv2.putText(img, "OpenCV", (500, 350), font, 3, (255, 0, 130), 5, cv2.LINE_AA)

cv2.imshow('Screenshot', img)

cv2.waitKey(0)
cv2.destroyAllWindows()
Пример #6
0
import numpy as np
from cv2 import cv2

image = cv2.imread('lena.jpg', 1)
image = cv2.line(image, (0, 0), (255, 255), (0, 0, 255), 2)
image = cv2.arrowedLine(image, (0, 0), (255, 255), (0, 255, 255), 2)
image = cv2.rectangle(image, (25, 70), (200, 170), (0, 255, 0), 5)
image = cv2.circle(image, (447, 63), 63, (255, 0, 0), 5)
font = cv2.FONT_HERSHEY_SIMPLEX
image = cv2.putText(image, "OpenCV", (10, 500), font, 5, (255, 255, 255), 5,
                    cv2.LINE_AA)

cv2.imshow('image', image)

cv2.waitKey(0)
cv2.destroyAllWindows()
Пример #7
0
def show_little_map(lm, points_2d, motion, id, armor_color):
    '''
    显示小地图,并在地图上标记目标
    :param points_2d: 待标记的二维点坐标
    :return: None
    '''
    Red = 1
    Blue = 2
    Others = 3

    ratio = 0.5
    arrow_scale = 10
    cur_pic = lm.pic.copy()
    #基准点 即相机所在位置
    offset = (int(1 / 2 * lm.map_width), int(0.98 * lm.map_height))
    cv.circle(cur_pic, offset, 7, (0, 255, 0), 3)
    #小地图的缩放尺寸
    width = lm.get_width() * ratio
    height = lm.get_height() * ratio

    motion = np.array(motion)
    # print(width,height)
    #print("show_little_map : ")
    for i, point in enumerate(points_2d):
        # print("points_2d :",i," \n",points_2d)
        # print("motion : \n",motion[i])
        #当前运动趋势
        cur_motion = np.array(motion[i] * arrow_scale, dtype=np.int)
        #当前位置
        cur_position = (point[0], point[1])
        '''正常的投影变换 需要知道准确的相机高度与相机参数  ,所以先不用
                # scale_x = point[0]/(lm.count_width)*(lm.map_width)
                # scale_y = point[1]/(lm.count_height)*(lm.map_height)
                #
                # cur_position = (int( offset[0] + scale_x), int(offset[1]-scale_y))
                # print("scale : (",cur_position[0],",",cur_position[1],")")
                # print("point : (",point)
                # motion_direction = (point[0]+cur_motion[0] ,point[1]+cur_motion[1])
        '''
        #运动趋势
        motion_direction = (cur_position[0] + cur_motion[0],
                            cur_position[1] + cur_motion[1])
        #打印牌号
        label = '{}{:d}'.format("", id[i])
        cv.putText(cur_pic, label,
                   (cur_position[0] + 10, cur_position[1] + 10),
                   cv.FONT_HERSHEY_PLAIN, 2, [255, 255, 255], 2)

        color = armor_color[i]
        if (color == Red):
            circle_color = (0, 0, 255)
        elif (color == Blue):
            circle_color = (255, 0, 0)
        else:
            circle_color = (255, 255, 255)
        #打印所在位置与运动趋势
        cv.circle(cur_pic, cur_position, 10, circle_color, 2)
        cv.arrowedLine(cur_pic, cur_position, motion_direction, (0, 255, 0), 5,
                       8, 0, 0.3)

    cur_pic = cv.resize(cur_pic, (int(width), int(height)),
                        interpolation=cv.INTER_AREA)

    return cur_pic
Пример #8
0
# Make different shapes on image
from cv2 import cv2

img = cv2.imread('lena.jpg', 1)

img = cv2.line(img, (0, 0), (160, 160), (0, 255, 0), 10)  # Make a line

img = cv2.arrowedLine(img, (0, 0), (100, 100), (0, 0, 255),
                      10)  # Make an arrowed line

img = cv2.rectangle(img, (180, 180), (400, 400), (255, 0, 0),
                    7)  # Produce a rectangle

img = cv2.circle(img, (290, 290), 100, (255, 255, 0), -1)  # Produce a circle

# Note: If in above thickness=-1 is put then it will cover the whole figure as in case of circle

# Writing a text on the image
img = cv2.putText(img, "HOTT Sensation!!", (10, 450), cv2.FONT_HERSHEY_SIMPLEX,
                  0.6, (0, 0, 255), 2)

cv2.imshow('window1', img)

if cv2.waitKey(0) == 27:
    cv2.destroyAllWindows()
Пример #9
0
n_frames = file_size // (width * height * 2)
prevFrame = None
f = open(yuv_filename, 'rb')
yuv = np.frombuffer(f.read(width * height * 2),
                    dtype=np.uint8).reshape(height, width, 2)
prevFrame = cv2.cvtColor(yuv, cv2.COLOR_YUV2BGR_YUYV)
yuv = np.frombuffer(f.read(width * height * 2),
                    dtype=np.uint8).reshape(height, width, 2)
frame = cv2.cvtColor(yuv, cv2.COLOR_YUV2BGR_YUYV)

f.close()

bcount = 0
blockSize = 8
for y in range(0, int(90 * 8), 8):
    for x in range(0, int(160 * 8), 8):
        if (x, y) != (vectors[bcount][0], vectors[bcount][1]):

            p = vectors[bcount]
            cv2.arrowedLine(
                frame, (p[0] + int(blockSize / 2), p[1] + int(blockSize / 2)),
                (x + int(blockSize / 2), y + int(blockSize / 2)), (0, 255, 0),
                1)
        bcount = bcount + 1
cv2.imshow("Vektori", frame)
cv2.waitKey()
# Convert YUV420 to Grayscale
#old_gray = cv2.cvtColor(old_yuv, cv2.COLOR_YUV2GRAY_I420)
#cv2.imshow('frame_gs',old_gray)
#cv2.waitKey()
Пример #10
0
        imgContours2, conts2 = utlis.getContours(imgWarp,
                                                 minArea=2000,
                                                 filter=4,
                                                 cThr=[50, 50],
                                                 draw=False)

        if len(conts) != 0:
            for obj in conts2:
                cv2.polylines(imgContours2, [obj[2]], True, (0, 255, 0), 2)
                nPoints = utlis.reorder(obj[2])
                nW = round((utlis.findDis(nPoints[0][0] // scale,
                                          nPoints[1][0] // scale) / 10), 1)
                nH = round((utlis.findDis(nPoints[0][0] // scale,
                                          nPoints[2][0] // scale) / 10), 1)
                cv2.arrowedLine(imgContours2,
                                (nPoints[0][0][0], nPoints[0][0][1]),
                                (nPoints[1][0][0], nPoints[1][0][1]),
                                (255, 0, 255), 3, 8, 0, 0.05)
                cv2.arrowedLine(imgContours2,
                                (nPoints[0][0][0], nPoints[0][0][1]),
                                (nPoints[2][0][0], nPoints[2][0][1]),
                                (255, 0, 255), 3, 8, 0, 0.05)
                x, y, w, h = obj[3]
                cv2.putText(imgContours2, '{}cm'.format(nW), (x + 30, y - 10),
                            cv2.FONT_HERSHEY_COMPLEX_SMALL, 1.5, (255, 0, 255),
                            2)
                cv2.putText(imgContours2, '{}cm'.format(nH),
                            (x - 70, y + h // 2),
                            cv2.FONT_HERSHEY_COMPLEX_SMALL, 1.5, (255, 0, 255),
                            2)
        cv2.imshow('Size Of Image', imgContours2)
    img = cv2.resize(img, (0, 0), None, 0.5, 0.5)
Пример #11
0
def draw_detected_objects(frame, detected_objects: List[DetectedObject]):
    cv2.putText(frame, "Number of Detected Objects: " + str(len(detected_objects)), (0, 15), cv2.FONT_HERSHEY_SIMPLEX,
                0.5, [0, 0, 255], 2)

    for detected_object in detected_objects:
        if detected_object.distance.measured:
            color = [255, 0, 0]
        elif detected_object.object_type == DetectedObjectType.SquareTimber:
            color = [255, 0, 255]
        else:
            color = [0, 255, 0]
        # draw bounding box
        min_point = (int(detected_object.bounding_box.min_x), int(detected_object.bounding_box.min_y))
        max_point = (int(detected_object.bounding_box.max_x), int(detected_object.bounding_box.max_y))
        cv2.rectangle(frame, min_point, max_point, color, 1)

        cv2.putText(frame, _determine_object_type_string_representation(detected_object.object_type),
                    (min_point[0], min_point[1] - 45), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
                    color, 2)

        cv2.putText(frame, str(detected_object.distance), (min_point[0], min_point[1] - 25), cv2.FONT_HERSHEY_SIMPLEX,
                    0.5, color, 2)
        cv2.putText(frame, "Probability [" + str(detected_object.probability) + "]", (min_point[0], min_point[1] - 5),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)

        for relative_object in detected_object.relative_detected_objects_from_relative_type(
                RelativeObjectType.IN_FRONT):
            obj_bbox = detected_object.bounding_box
            rel_obj_bbox = relative_object.bounding_box
            start_point = (int(obj_bbox.center_x()), int(obj_bbox.center_y()))
            end_point = (int(rel_obj_bbox.center_x()), int(rel_obj_bbox.center_y()))
            frame = cv2.arrowedLine(frame, start_point, end_point, [30, 30, 160], 2)
            cv2.putText(frame, "IN_FRONT_OF",
                        (end_point[0], end_point[1]), cv2.FONT_HERSHEY_SIMPLEX, 0.5, [0, 0, 255], 2)

        for relative_object in detected_object.relative_detected_objects_from_relative_type(
                RelativeObjectType.BEHIND):
            obj_bbox = detected_object.bounding_box
            rel_obj_bbox = relative_object.bounding_box
            start_point = (int(obj_bbox.center_x()), int(obj_bbox.center_y()))
            end_point = (int(rel_obj_bbox.center_x()), int(rel_obj_bbox.center_y()))
            frame = cv2.arrowedLine(frame, start_point, end_point, [30, 30, 160], 2)
            cv2.putText(frame, "BEHIND",
                        (end_point[0], end_point[1]), cv2.FONT_HERSHEY_SIMPLEX, 0.5, [60, 0, 255], 2)

        for relative_object in detected_object.relative_detected_objects_from_relative_type(
                RelativeObjectType.RIGHT):
            obj_bbox = detected_object.bounding_box
            rel_obj_bbox = relative_object.bounding_box
            start_point = (int(obj_bbox.max_x), int(obj_bbox.min_y + obj_bbox.height / 4))
            end_point = (int(rel_obj_bbox.min_x), int(rel_obj_bbox.min_y + rel_obj_bbox.height / 4))
            frame = cv2.arrowedLine(frame, start_point, end_point, [30, 30, 160], 2)
            cv2.putText(frame, "RIGHT",
                        (end_point[0], end_point[1]), cv2.FONT_HERSHEY_SIMPLEX, 0.5, [0, 0, 255], 2)

        for relative_object in detected_object.relative_detected_objects_from_relative_type(
                RelativeObjectType.LEFT):
            obj_bbox = detected_object.bounding_box
            rel_obj_bbox = relative_object.bounding_box
            start_point = (int(obj_bbox.min_x), int(obj_bbox.min_y + obj_bbox.height / 4))
            end_point = (int(rel_obj_bbox.max_x), int(rel_obj_bbox.min_y + rel_obj_bbox.height / 4))
            frame = cv2.arrowedLine(frame, start_point, end_point, [30, 30, 160], 2)
            cv2.putText(frame, "LEFT",
                        (end_point[0], end_point[1]), cv2.FONT_HERSHEY_SIMPLEX, 0.5, [0, 0, 255], 2)
Пример #12
0
def main():
    parser = argparse.ArgumentParser(
        description="combine two images with an arrow in between. Spacing and color is automatically decided and is meant to be nice"
    )

    parser.add_argument(
        "image_file_1", action="store", type=str, help="the image file in the left"
    )
    parser.add_argument(
        "image_file_2", action="store", type=str, help="the image file in the right"
    )
    parser.add_argument(
        "--output",
        "-o",
        action="store",
        required=False,
        type=str,
        help="the output image file. (e.g. out.jpg out.png) If omitted, <img1>-<img2>.png will be generated under current directory",
    )

    parser.add_argument(
        "--scale",
        "-s",
        required=False,
        default=1.0,
        action="store",
        type=float,
        help="the scale of the generated image, 1 for no scaling. 0.5 for half the size, etc",
    )

    argv = parser.parse_args()

    img1 = cv2.imread(argv.image_file_1, 1)
    img2 = cv2.imread(argv.image_file_2, 1)

    s_height = min(img1.shape[0], img2.shape[0])
    b_height = max(img1.shape[0], img2.shape[0])

    s_width = min(img1.shape[1], img2.shape[1])
    b_width = max(img1.shape[1], img2.shape[1])

    frame = np.full((b_height, 2 * s_width + b_width, 3), 255, dtype=np.uint8)

    place_on_top(img1, frame, [(b_height - img1.shape[0]) // 2, 0])
    place_on_top(
        img2, frame, [(b_height - img2.shape[0]) // 2, s_width + img1.shape[1]]
    )

    m1 = cv2.mean(img1)
    m2 = cv2.mean(img2)

    mean_color = []
    for i in range(3):
        mean_color.append(int(m1[i] + m2[i]) // 2)

    cv2.arrowedLine(
        frame,
        (img1.shape[1] + s_width // 5, b_height // 2),
        (img1.shape[1] + s_width - s_width // 5, b_height // 2),
        mean_color,
        8,
        tipLength=0.6,
    )

    assert argv.scale > 0, "scale has to be a positive float"
    frame = cv2.resize(
        frame, (int(frame.shape[1] * argv.scale), int(frame.shape[0] * argv.scale))
    )

    outname = argv.output
    if argv.output is not None:
        try:
            cv2.imwrite(argv.output, frame)
        except cv2.error as e:
            print(e, file=stderr)
            print("Failed to save the image")
            print("Did you forget to specify image format to the output file?")
    else:
        default_name = (
            path.splitext(path.basename(argv.image_file_1))[0]
            + "-"
            + path.splitext(path.basename(argv.image_file_2))[0]
            + ".png"
        )
        outname = default_name
        cv2.imwrite(default_name, frame)

    cv2.imshow(outname, frame)
    while cv2.getWindowProperty(outname, cv2.WND_PROP_VISIBLE) == 1:
        if cv2.waitKey(50) != -1:
            break

    cv2.destroyAllWindows()
Пример #13
0
import numpy as np
from cv2 import cv2

img = cv2.imread('lena.png', -1)
img = np.zeros([512, 512, 3], np.uint8)  # Imagem preta

# Linha
img = cv2.line(img, (0, 0), (255, 255), (255, 0, 0), 2)

# Seta
img = cv2.arrowedLine(img, (0, 255), (255, 255), (0, 255, 0), 2)

# Quadrado
img = cv2.rectangle(img, (384, 0), (510, 128), (0, 0, 255), 2)

# Circulo
img = cv2.circle(img, (447, 63), (63), (255, 255, 255), 2)

# Texto
font = cv2.FONT_HERSHEY_SIMPLEX
img = cv2.putText(img, 'Texto', (10, 500), font, 4, (0, 255, 0), 3,
                  cv2.LINE_AA)

cv2.imshow('image', img)

cv2.waitKey(0)
cv2.destroyAllWindows()