def run(video_file, tracker_type):
video = cv2.VideoCapture(video_file)
if not video.isOpened():
sys.exit()
colors = []
tracker = None
fps = None
while True:
ok, frame = video.read()
if not ok:
break
if not video_file:
frame = cv2.flip(frame, 1, 0)
key_code = cv2.waitKey(1)
if key_code == ord('q'):
break
elif key_code == ord(' '):
bboxs = cv2.selectROIs(WINDOW_NAME, frame, showCrosshair=False)
if len(bboxs):
tracker, colors = get_multi_tracker(tracker_type, frame, bboxs)
else:
tracker = None
if tracker:
tracker_update(frame, tracker, colors)
cv2.imshow(WINDOW_NAME, frame)
def main():
ROIs = cv2.selectROIs('Select -> <Enter> -> Select -> <Enter> -> <Esc>',
IMAGE,
fromCenter=False) # (xmin, ymin, w, h)
ROI_bboxes = list(map(convert_roi_to_bbox, ROIs))
[print(f'Box {i}: {bbox}') for i, bbox in enumerate(ROI_bboxes)]
def select_rois_over_image(cls, im, save_to, delimiter, quotechar):
""""""
print("------------------------------------------------------------")
print("If there are no ROIs being selected,")
print("Pressing ESC will create 1 ROI with the size of whole image.")
print("------------------------------------------------------------")
rois = cv.selectROIs("Select ROIs", im)
if len(rois) == 0:
h, w, __ = im.shape
rois = [[0, 0, w, h]]
with open(save_to, "w+", newline="") as csvfile:
writer = csv.DictWriter(
csvfile,
fieldnames=cls.fields.keys(),
delimiter=delimiter,
quotechar=quotechar,
quoting=csv.QUOTE_NONNUMERIC,
)
writer.writeheader()
print("ROIs data:")
for roi_n, roi_val in enumerate(rois):
x, y, w, h = roi_val
roi = cls.create_roi([roi_n, x, y, w, h])
cls.add_default(roi)
writer.writerow(roi)
print(roi)
def get_color_stats(bgr, hsv):
"""
Allows the user to select rectangular regions in an img that represents a color class
and returns the stats (mu, std) for the color values in hsv space
"""
crop = np.empty((0, 3))
for x, y, ww, hh in cv2.selectROIs("", bgr):
_crop = hsv[y:y + hh, x:x + ww].reshape(-1, 3)
crop = np.concatenate((crop, _crop), axis=0)
h, s, v = crop.transpose()
# hue values wrap around. So we take the hue vector mean
# and convert it back to a hue value
_h = h * math.pi * 2
hc, hs = np.cos(_h), np.sin(_h)
hmu = (math.atan2(hs.mean(), hc.mean()) / (math.pi * 2)) % 1
# center hue values around the mean to get a correct std
_h = h.copy()
if hmu < 0.5:
_h[_h > hmu + 0.5] -= 1
else:
_h[_h < hmu - 0.5] += 1
crop = np.stack([_h, s, v], axis=-1)
mu, std = crop.mean(axis=0), crop.std(axis=0)
mu[0] = hmu
return mu, std
def OnBtnSelectAreaClicked(self):
rgb_frame = self._current_frame
cv2.cvtColor(rgb_frame, cv2.COLOR_RGB2BGR, rgb_frame)
self._areas = cv2.selectROIs('Select Area', self._current_frame, False)
cv2.destroyWindow('Select Area')
frame = cvrect.draw_rects(self._current_frame, self._areas,
(0, 0, 255))
frame = cvrect.draw_lines(frame, self._lines, (0, 0, 255))
self.SetTrackingFrame(frame)
def draw_boxes(images):
all_rois = []
for im in images:
rois = {}
for roi_type in ['text', 'checkbox', 'signature']:
print(roi_type)
rois[roi_type] = cv2.selectROIs("Image", im, False, False)
all_rois.append(rois)
return all_rois
def Select_Regions(frame):
ROA = np.array([])
ROIs = np.array([])
cv2.namedWindow('real image')
cv2.setMouseCallback('real image', draw, 0)
if path_roa:
key = input("Saved ROA detected. Press Enter if you want to proceed with it otherwise press anything and Enter")
if key == '':
#read from csv write into ROA
ROA = genfromtxt('ROA.csv', delimiter=',')
frame = frame[int(ROA[1]):int(ROA[1]+ROA[3]), int(ROA[0]):int(ROA[0]+ROA[2])]
else:
ROA_det = cv2.selectROI('Select Region of Area', frame, False)
ROA = np.array(ROA_det)
ROA = np.asarray(ROA)
np.savetxt("ROA.csv", ROA, delimiter=",")
cv2.destroyWindow('Select Region of Area')
frame = frame[int(ROA_det[1]):int(ROA_det[1]+ROA_det[3]), int(ROA_det[0]):int(ROA_det[0]+ROA_det[2])]
else:
ROA_det = cv2.selectROI('Select Region of Area', frame, False)
ROA = np.array(ROA_det)
ROA = np.asarray(ROA)
np.savetxt("ROA.csv", ROA, delimiter=",")
cv2.destroyWindow('Select Region of Area')
frame = frame[int(ROA_det[1]):int(ROA_det[1]+ROA_det[3]), int(ROA_det[0]):int(ROA_det[0]+ROA_det[2])]
if path_rois:
key = input("Saved ROIs detected. Press Enter if you want to proceed with it otherwise press anything and Enter")
if key == '':
#read from csv write into ROIs
ROIs = genfromtxt('ROIs.csv', delimiter=',')
else:
cv2.imshow('real image', frame)
if cv2.waitKey(20) & 0xFF == ord('q'):
print(ix)
print(iy)
#print(boxes)
while True:
a = 2
'''
ROIs = cv2.selectROIs('Select Region of interests', frame, False)
ROIs = np.array(ROIs)
ROIs = np.asarray(ROIs)
np.savetxt("ROIs.csv", ROIs, delimiter=",")
cv2.destroyWindow('Select Region of interests')
'''
else:
ROIs = cv2.selectROIs('Select Region of interests', frame, False)
ROIs = np.array(ROIs)
ROIsA = np.asarray(ROIs)
np.savetxt("ROIs.csv", ROIs, delimiter=",")
cv2.destroyWindow('Select Region of interests')
return ROA , ROIs
def select_multiple_roi(img):
"""
DOES NOT WORK
"""
regions = cv2.selectROIs("Select regions", img, False, False)
for r in regions:
cv2.rectangle(img, (r[0], r[1]), (r[2] + r[0], r[3] + r[1]),
(255, 0, 0), 2)
cv2.imshow("image", img)
cv2.waitKey(0)
def init_rects_from_raid(name):
raid_screenshot = get_screen()
from_center = False
show_crosshair = False
rects = cv2.selectROIs(name,
raid_screenshot,
fromCenter=from_center,
showCrosshair=show_crosshair)
points = [Point(rect[0], rect[1], rect[2], rect[3]) for rect in rects]
cv2.destroyAllWindows()
return points
def multi_rois(im):
# Select multiple ROI
roi = cv2.selectROIs("Image", im, 0, 0)
for i in range(len(roi)):
# Crop image
im_crop = im[int(roi[i][1]):int(roi[i][1] + roi[i][3]),
int(roi[i][0]):int(roi[i][0] + roi[i][2])]
# Show the image
cv2.imshow("Cropped Image: " + str(i), im_crop)
def roi_select(array,
toast_title,
winName="ERROR YOU HAVEN'T NAMED THIS WINDOW!!"):
rois = cv2.selectROIs(winName,
array,
showCrosshair=False,
fromCenter=False)
cv2.destroyAllWindows()
toaster.show_toast(toast_title,
"Captured %s ROI's" % (len(rois)),
duration=2)
return rois
def GetROI(img):
imgCounter = img.copy()
cv2.putText(imgCounter,
'Please select a part of a counter and press Enter', (1, 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.75, (255, 255, 255), 2,
cv2.LINE_AA)
cv2.putText(imgCounter, 'Press Esc when you finished', (1, 40),
cv2.FONT_HERSHEY_SIMPLEX, 0.75, (255, 255, 255), 2,
cv2.LINE_AA)
counter = cv2.selectROIs('Counter', imgCounter, False)
cv2.destroyAllWindows()
return counter
def cortarImagen(self):
self.comboNuevasRegiones.clear()
self.recorteLabel.hide()
self.continuarbtn.hide()
self.puntos = []
listaPuntos = []
ROIs = []
self.aux = self.imagen.copy()
cv2.namedWindow("Imagen", cv2.WINDOW_NORMAL)
cv2.resizeWindow("Imagen", self.anchoImg, self.alturaImg)
ROIs = cv2.selectROIs("Imagen", self.aux)
cv2.destroyWindow("Imagen")
for rect in ROIs: #Añade todos los recortes a la variable puntos
x1 = int(rect[0])
y1 = int(rect[1])
x2 = int(rect[2])
y2 = int(rect[3])
listaPuntos = [[x1, y1], [(x2 + x1), y1], [x1, (y1 + y2)],
[(x1 + x2), (y1 + y2)]]
self.puntos.append(listaPuntos)
#
for i in range(len(ROIs)):
self.comboNuevasRegiones.addItem("Region " + str(i + 1))
if len(self.puntos) >= 1:
self.dst = recortarImagen(self.aux, self.puntos[0])
self.cortarImagenbtn.show()
self.guardarbtn.show()
self.comboNuevasRegiones.show()
self.labelRegionMsg.show()
self.imagenPixMap = formatoPixMap(self.dst)
imgW = round(37 / 100 * self.anchowin)
imgH = round(68 / 100 * self.alturawin)
self.imagenPixMap = self.imagenPixMap.scaled(imgW, imgH)
self.recorteLabel.setPixmap(self.imagenPixMap)
self.recorteLabel.show()
self.move(50, 50)
self.textLabel.hide()
else:
self.cortarImagenbtn.hide()
self.guardarbtn.hide()
self.comboNuevasRegiones.hide()
self.labelRegionMsg.hide()
self.textLabel.show()
self.continuarbtn.show()
msg = QMessageBox()
msg.setText(
"Las regiones no se guardaron correctamente, porfavor seguir las instrucciones mostradas en pantalla"
)
msg.setWindowTitle("Error")
msg.exec_()
def configure(self, camera):
print('Configuration starting..')
frame = camera.getSingleFrame()
print('Select the reference region')
template_regions = cv2.selectROIs(
'Select the reference region(s), enter to confirm spot, esc to close',
frame)
for template_region in template_regions:
self.template_regions.append(template_region)
cv2.destroyAllWindows()
print('Select spots')
regions = cv2.selectROIs(
'Select spots, enter to confirm spot, esc to close', frame)
spot_id = 1 # Spots start at 1
for region in regions:
self.parking_spots.append(
ParkingLotSpot(spot_id, (region[0], region[1]),
(region[0] + region[2], region[1] + region[3]),
region[2] / 3))
spot_id += 1
cv2.destroyAllWindows()
def selectROIs(frame, xa, ya):
print('identify nest area')
box_n = cv2.selectROIs("Frame", frame, fromCenter=False)
((xn, yn, wn, hn), ) = tuple(map(tuple, box_n))
nest_corners = {
'xmin': xn - xa,
'ymin': yn - ya,
'width': wn,
'height': hn,
}
cv2.destroyAllWindows()
return nest_corners
def ROI():
while True:
global r
ret, im0 = cap.read()
im0 = imutils.resize(im0, width=900)
showCrosshair = False
fromCenter = False
r = cv2.selectROIs("Image", im0, showCrosshair, fromCenter)
if (len(r) == 0):
cv2.putText(im0, 'Please select Region of interest', (10, 500),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
print('Selecrt intrusion')
else:
break
def MouseRoI(dirpath):
"""
openfaceのlandmarkを使って，顔領域を選択し平均化されたRGBを返す
"""
# ファイル一覧を取得
files = []
i = 0
for filename in os.listdir(dirpath):
if os.path.isfile(os.path.join(dirpath, filename)): #ファイルのみ取得
files.append(filename)
# マウスイベント
winname = 'Image'
image = cv2.imread(os.path.join(dirpath, files[816]))
rois = cv2.selectROIs(winname, image, False) # x,y,w,h
cv2.destroyAllWindows()
for r in rois:
print("x:{}, y:{}, w:{}, h:{}".format(r[0],r[1],r[2],r[3]))
# loop from first to last frame
for fname in files[816:]:
frame = cv2.imread(os.path.join(dirpath, fname))
j = 0
for r in rois:
img_roi = frame[int(r[1]):int(r[1]+r[3]), int(r[0]):int(r[0]+r[2])]
if j == 0:
ave_rgb_roi = AveragedRGB(img_roi)
else:
ave_rgb_roi = np.concatenate([ave_rgb_roi,AveragedRGB(img_roi)], axis=1)
j = j+1
if i == 0:
rgb_components = ave_rgb_roi
else:
rgb_components = np.concatenate([rgb_components, ave_rgb_roi], axis=0)
# plot
for r in rois:
cv2.rectangle(frame,(r[0],r[1]),(r[2]+r[0],r[3]+r[1]), (255, 0, 0),thickness=3)
cv2.imshow("frame", frame)
i = i + 1
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()
return rgb_components
def create_rois_list(window_title, crops, full_image, project_size=10):
shrink_factor = 5
resized = cv2.resize(full_image, (0, 0),
fx=1 / shrink_factor,
fy=1 / shrink_factor)
rois = cv2.selectROIs(window_title, resized)
cv2.destroyAllWindows()
if type(rois) is not tuple:
rois = [Rect(*roi) for roi in (rois * shrink_factor).tolist()]
crops = [[
crop for crop in crops
if Rect(crop[1][1], crop[1][0], crop[0].shape[1],
crop[0].shape[0]).intersection(r).area() > 0
] for r in rois]
return crops
else:
return []
def imageClickRegions(image_name, image_wh_tuple):
img = cv.imread("image_name")
img = cv.resize(img, dsize=image_wh_tuple, interpolation=cv.INTER_AREA)
button_areas = cv.selectROIs("Enter to confirm", img, True, False)
print('button_areas =', button_areas)
for r in button_areas:
cv.rectangle(img, (r[0], r[1]), (r[0] + r[2], r[1] + r[3]), 255)
## img = img[r[1]:r[1]+r[3], r[0]:r[0]+r[2]]
## cv.imshow('Img', img)
## cv.waitKey()
cv.imshow('img', img)
cv.waitKey()
cv.destroyAllWindows()
return button_areas
def select_roi(self):
self.set_button_false() # 把视频暂停了
if self.vth.frame is None:
cap = cv2.VideoCapture(video_path)
frame = self.vth.adjust_frame(cap.read()[1])
cap.release()
else:
frame = self.vth.frame.copy()
cv2.namedWindow('Select ROI', cv2.WINDOW_NORMAL)
print('选择一个roi，按下space或enter键后确认选择，继续选择下一个roi，全部选择结束后按Esc键退出')
bboxes = cv2.selectROIs("Select ROI",
frame,
fromCenter=False,
showCrosshair=True)
cv2.destroyWindow('Select ROI')
if not isinstance(bboxes, tuple):
bboxes[:, 2:4] = bboxes[:, 0:2] + bboxes[:, 2:4]
self.vth.CF.roi_list = bboxes
def select_box(self): # 手动绘制待跟踪目标
self.set_button_false() # 把视频暂停了
if self.vth.frame is None:
cap = cv2.VideoCapture(video_path)
frame = self.vth.adjust_frame(cap.read()[1])
cap.release()
else:
frame = self.vth.frame.copy()
cv2.namedWindow('MultiTracker', cv2.WINDOW_NORMAL)
print('选择一个目标，按下space或enter键后确认选择，继续选择下一个目标，全部选择结束后按Esc键退出')
bboxes = cv2.selectROIs("MultiTracker",
frame,
fromCenter=False,
showCrosshair=True)
cv2.destroyWindow('MultiTracker')
for bbox in bboxes:
self.vth.CF.multiTracker.add(cv2.TrackerKCF_create(), frame,
tuple(bbox))
self.vth.CF.car_num += 1
def manual_face_selection(self, image):
'''
Handles the manual selection of faces bounding boxes in case the Viola-Jones algorithm
misses them. Once the user selects the rectangles, these are obscured with the same
policy applied fo the others.
'''
fromCenter = False
showCrossHair = True
rois = cv2.selectROIs("", image, showCrossHair, fromCenter)
for roi in rois:
self.final_image = cv2.rectangle(
self.final_image, (roi[0], roi[1]),
(roi[0] + roi[2], roi[1] + roi[3]), (0, 255, 0), 2)
self.final_image[roi[1]:roi[1] + roi[3],
roi[0]:roi[0] + roi[2]] = cv2.blur(
self.final_image[roi[1]:roi[1] + roi[3],
roi[0]:roi[0] + roi[2]],
(40, 40))
def initialVideo(filename, t_type='KCF'):
video = cv2.VideoCapture(filename)
if filename == 0:
while True:
ret, frame = video.read()
cv2.imshow("Press A to start", frame)
k = cv2.waitKey(1)
if k == ord('a'):
cv2.destroyAllWindows()
break
success, firstframe = video.read()
multiTracker = []
boxes = cv2.selectROIs("Select", firstframe, False, False)
for box in boxes:
box = tuple(box)
tracker = TrackerDefine(t_type)
tracker.init(firstframe, box)
multiTracker.append(tracker)
cv2.destroyAllWindows()
return video, multiTracker[:3], boxes[:3], firstframe
def getRoisDetectionImage(self,image):
ROIs = cv2.selectROIs("Select Rois",image)
#print rectangle points of selected roi
print(ROIs)
#Crop selected roi ffrom raw image
#counter to save image with different name
crop_number=0
#loop over every bounding box save in array "ROIs"
for rect in ROIs:
x1=rect[0]
y1=rect[1]
x2=rect[2]
y2=rect[3]
#crop roi from original image
img_crop=image[y1:y1+y2,x1:x1+x2]
cv2.imwrite("crop"+str(crop_number)+".jpeg",img_crop)
#show cropped image
crop_number+=1
def createSel(img):
'''
Parameters
----------
img : path to the image on wich to perform the ROI selection
Returns
-------
imgCrop : the cropped image, as an array (cv2 or numpy)
Coords : the coordinates of the selection as follows (row, row+rowheight, col, col+colwidth)
'''
#cv2.startWindowThread()
#img = cv2.imread(img)
#band_dict = get_band([band_id],folder)
#img = band_dict[band_id]
ROIs = cv2.selectROIs(
"Select the ROI : Click and drag the mouse (top left to bottom right) and press Enter, or c to cancel",
img)
coords_list = list()
#print(ROIs)
for ROI in ROIs:
#imgCrop = img[int(ROI[1]):int(ROI[1]+ROI[3]), int(ROI[0]):int(ROI[0]+ROI[2])]
coords_list.append([
int(ROI[1]),
int(ROI[1] + ROI[3]),
int(ROI[0]),
int(ROI[0] + ROI[2])
])
#cv2.imshow("Image", imgCrop)
#cv2.waitKey(0)
#cv2.destroyAllWindows()
#print(Coords_list)
cv2.destroyAllWindows()
#label = create_label(img, coords_list, False)
#if save:
# path = save_label(label, band_dict['folder'])
print(coords_list)
return coords_list
def MouseRoIVideo(cap):
"""
openfaceのlandmarkを使って，顔領域を選択し平均化されたRGBを返す
"""
# マウスイベント
winname = 'Image'
ret, image = cap.read()
rois = cv2.selectROIs(winname, image, False) # x,y,w,h
cv2.destroyAllWindows()
for r in rois:
print("x:{}, y:{}, w:{}, h:{}".format(r[0],r[1],r[2],r[3]))
# loop from first to last frame
for i in range(int(cap.get(cv2.CAP_PROP_FRAME_COUNT))-1):
j = 0
#for fname in files:
print("Frame: {}/{}".format(i,cap.get(cv2.CAP_PROP_FRAME_COUNT)))
ret, frame = cap.read()
for r in rois:
img_roi = frame[int(r[1]):int(r[1]+r[3]), int(r[0]):int(r[0]+r[2])]
if j == 0:
ave_rgb_roi = AveragedRGB(img_roi)
else:
ave_rgb_roi = np.concatenate([ave_rgb_roi,AveragedRGB(img_roi)], axis=1)
j = j+1
if i == 0:
rgb_components = ave_rgb_roi
else:
rgb_components = np.concatenate([rgb_components, ave_rgb_roi], axis=0)
# cv2.imshow("frame", mask_img)
i = i + 1
if cv2.waitKey(1) & 0xFF == ord('q'):
break
print(i)
cv2.destroyAllWindows()
return rgb_components
def label_dataset(num_of_imgs: int):
"""
A function using selectROI to label stream of images and saves it as jpg image.
:param num_of_imgs (int): Number of images to label
"""
for i in range(num_of_imgs):
image_name = "TestingImages/" + str(i) + ".jpg"
img_raw = cv2.imread(image_name)
cv2.imshow("IMAGE " + str(i), img_raw)
cv2.waitKey(0)
cv2.destroyAllWindows()
print("Enter number of regions (N):")
num_of_reg = int(input())
print("Number of regions = " + str(num_of_reg) +
". \n Create rectangles and after each rectangle press ENTER."
" When done, press ESC to finish labeling this region. "
"Repeat for each region.")
labels_arr = np.zeros((img_raw.shape[0], img_raw.shape[1]))
for label_id in range(1, num_of_reg + 1):
print("Label Region #" + str(label_id))
while True:
boundingBoxes = cv2.selectROIs(
"LABEL REGION #" + str(label_id), img_raw)
if not isinstance(boundingBoxes, tuple):
print("Region " + str(label_id) + " labeled")
for row in boundingBoxes:
labels_arr[row[1]:row[1] + row[3], row[0]:row[0] +
row[2]] = label_id / num_of_reg
cv2.destroyAllWindows()
break
else:
print("No Region Selected. Please select Region " +
str(label_id))
cv2.imshow("Labels Array", labels_arr)
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.imwrite("TestingImages/" + str(i) + "_label.jpg", labels_arr * 255)
np.savez("TestingImages/" + str(i) + "_label", labels_arr)
def tracker_init(self, image):
"""
用于进行目标跟踪初始化
都采用KCF的方法进行跟踪,其他的方法并不好用
:param image: 初始化的图片
:param track_method: 跟踪算法(默认为KCF)
:return:
"""
#每一次初始化,都把以前的跟踪目标给重置,要不然越add越多
self.tracker = cv.MultiTracker_create()
category_num = 10 #默认最多不超过10个类
#1:进行bboxes的选择
cv.namedWindow("ROI", cv.WINDOW_FULLSCREEN)
select_bboxes = cv.selectROIs("ROI", image)
bboxes = []
#1.1bboxes中的所有bbox转成tuple类型
for bbox in select_bboxes:
x, y, w, h = bbox
bboxes.append((x, y, w, h))
#2:输入跟踪类别id
print("请在图片中输入种类id")
while True:
info_input = cv.waitKey()
info_input = int(info_input) - 48
if -1 < info_input < category_num: #在所有种类中则完成输入
self.tracker_category_id = info_input
break
else: #避免输入其他错误参数
print("请输入一个介于0到{}之间的数字".format(category_num))
#3:进行目标添加
for bbox in bboxes:
self.tracker.add(cv.TrackerKCF_create(), image, bbox)
cv.destroyWindow("ROI")
return bboxes
def select_rois_over_image(cls, im, save_to, delimiter, quotechar,
quoting):
"""Select ROIs over a ndarray image.
Args:
im (ndarray): image to select ROIs over.
save_to (str): csv file path to save ROIs data to.
delimiter (str): delimiter.
quotechar (str): quote char.
quoting (csv.QUOTE_xxx constant): quoting instruction.
"""
print("------------------------------------------------------------")
print("If there are no ROIs being selected,")
print("Pressing ESC will create 1 ROI with the size of whole image.")
print("------------------------------------------------------------")
rois = cv.selectROIs("Select ROIs", im)
if len(rois) == 0:
h, w, __ = im.shape
rois = [[0, 0, w, h]]
with open(save_to, "w+", newline="") as csvfile:
writer = csv.DictWriter(
csvfile,
fieldnames=cls.default.keys(),
delimiter=delimiter,
quotechar=quotechar,
quoting=quoting,
)
writer.writeheader()
print("ROIs data:")
for roi_n, roi_val in enumerate(rois):
x, y, w, h = roi_val
roi_data = cls.create_roi_data([roi_n, x, y, w, h])
cls.add_default(roi_data)
writer.writerow(roi_data)
print(roi_data)
def annotateImages(dir, labels): for path in os.listdir(dir): # read and display next image in directory img = cv2.imread(os.path.join(dir, path)) cv2.imshow(path, img) # allow user to select multiple regions of interest boxes = cv2.selectROIs(path, img, FROM_CENTER, SHOW_CROSSHAIR) cv2.destroyAllWindows() # allow user to label each box drawn for box in boxes: root = tkinter.Tk() # show image within box in window with dropdown to select label box_img = img[box[1]:box[1]+box[3], box[0]:box[0]+box[2]] box_img = ImageTk.PhotoImage(image=Image.fromarray(box_img)) canvas = tkinter.Canvas(root, width=300, height=300) canvas.pack() canvas.create_image(20,20, anchor="nw", image=box_img) root.mainloop()
