Python cv2.RETR_CCOMP Examples
The following are 30
code examples of cv2.RETR_CCOMP().
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Example #1
| Source File: vis.py From Parsing-R-CNN with MIT License | 7 votes |
|
def vis_parsing(img, parsing, colormap, show_segms=True):
"""Visualizes a single binary parsing."""
img = img.astype(np.float32)
idx = np.nonzero(parsing)
parsing_alpha = cfg.VIS.SHOW_PARSS.PARSING_ALPHA
colormap = colormap_utils.dict2array(colormap)
parsing_color = colormap[parsing.astype(np.int)]
border_color = cfg.VIS.SHOW_PARSS.BORDER_COLOR
border_thick = cfg.VIS.SHOW_PARSS.BORDER_THICK
img[idx[0], idx[1], :] *= 1.0 - parsing_alpha
# img[idx[0], idx[1], :] += alpha * parsing_color
img += parsing_alpha * parsing_color
if cfg.VIS.SHOW_PARSS.SHOW_BORDER and not show_segms:
_, contours, _ = cv2.findContours(parsing.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, border_color, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #2
| Source File: vis.py From Parsing-R-CNN with MIT License | 7 votes |
|
def vis_mask(img, mask, bbox_color, show_parss=False):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
border_color = cfg.VIS.SHOW_SEGMS.BORDER_COLOR
border_thick = cfg.VIS.SHOW_SEGMS.BORDER_THICK
mask_color = bbox_color if cfg.VIS.SHOW_SEGMS.MASK_COLOR_FOLLOW_BOX else _WHITE
mask_color = np.asarray(mask_color)
mask_alpha = cfg.VIS.SHOW_SEGMS.MASK_ALPHA
_, contours, _ = cv2.findContours(mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
if cfg.VIS.SHOW_SEGMS.SHOW_BORDER:
cv2.drawContours(img, contours, -1, border_color, border_thick, cv2.LINE_AA)
if cfg.VIS.SHOW_SEGMS.SHOW_MASK and not show_parss:
img[idx[0], idx[1], :] *= 1.0 - mask_alpha
img[idx[0], idx[1], :] += mask_alpha * mask_color
return img.astype(np.uint8)
Example #3
| Source File: vis.py From nuke-ML-server with Apache License 2.0 | 6 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
# cv2.findContours gives (image, contours, hierarchy) back in opencv 3.x
# but gives back (contours, hierachy) in opencv 2.x and 4.x
contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)[-2:]
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #4
| Source File: vis.py From DetectAndTrack with Apache License 2.0 | 6 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick,
cv2.CV_AA if cv2.__version__.startswith('2') else
cv2.LINE_AA)
return img.astype(np.uint8)
Example #5
| Source File: viz.py From Object_Detection_Tracking with Apache License 2.0 | 6 votes |
|
def draw_mask(im, mask, alpha=0.5, color=None, show_border=True,border_thick=1):
"""
Overlay a mask on top of the image.
Args:
im: a 3-channel uint8 image in BGR
mask: a binary 1-channel image of the same size
color: if None, will choose automatically
"""
if color is None:
color = PALETTE_RGB[np.random.choice(len(PALETTE_RGB))][::-1]
im = np.where(np.squeeze(np.repeat((mask > 0)[:, :, None], 3, axis=2)),
im * (1 - alpha) + color * alpha, im)
if show_border:
if cv2.__version__.startswith("2"):
contours, _ = cv2.findContours(mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
else: # cv 3
_,contours, _ = cv2.findContours(mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(im, contours, -1, (255,255,255), border_thick, lineType=cv2.CV_AA)
im = im.astype('uint8')
return im
Example #6
| Source File: visualize.py From ExtremeNet with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=2):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
# How to use `cv2.findContours` in different OpenCV versions?
# https://stackoverflow.com/questions/48291581/how-to-use-cv2-findcontours-in-different-opencv-versions/48292371#48292371
contours = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)[-2]
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #7
| Source File: idcardocr.py From idmatch with MIT License | 6 votes |
|
def recognize_text(original):
idcard = original
# gray = cv2.cvtColor(idcard, cv2.COLOR_BGR2GRAY)
# Morphological gradient:
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
opening = cv2.morphologyEx(idcard, cv2.MORPH_GRADIENT, kernel)
# Binarization
ret, binarization = cv2.threshold(opening, 0.0, 255.0, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
# Connected horizontally oriented regions
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9, 1))
connected = cv2.morphologyEx(binarization, cv2.MORPH_CLOSE, kernel)
# find countours
_, contours, hierarchy = cv2.findContours(
connected, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE
)
return contours, hierarchy
Example #8
| Source File: img.py From HUAWEIOCR-2019 with MIT License | 5 votes |
|
def find_contours(mask, method = None):
if method is None:
method = cv2.CHAIN_APPROX_SIMPLE
mask = np.asarray(mask, dtype = np.uint8)
mask = mask.copy()
try:
contours, _ = cv2.findContours(mask, mode = cv2.RETR_CCOMP,
method = method)
except:
_, contours, _ = cv2.findContours(mask, mode = cv2.RETR_CCOMP,
method = method)
return contours
Example #9
| Source File: img.py From HUAWEIOCR-2019 with MIT License | 5 votes |
|
def find_two_level_contours(mask):
mask = mask.copy()
contours, tree = cv2.findContours(mask, mode = cv2.RETR_CCOMP,
method = cv2.CHAIN_APPROX_SIMPLE)
return contours, tree
Example #10
| Source File: vis.py From wifiperson with MIT License | 5 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
_, contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #11
| Source File: img.py From HUAWEIOCR-2019 with MIT License | 5 votes |
|
def find_contours(mask, method = None):
if method is None:
method = cv2.CHAIN_APPROX_SIMPLE
mask = np.asarray(mask, dtype = np.uint8)
mask = mask.copy()
try:
contours, _ = cv2.findContours(mask, mode = cv2.RETR_CCOMP,
method = method)
except:
_, contours, _ = cv2.findContours(mask, mode = cv2.RETR_CCOMP,
method = method)
return contours
Example #12
| Source File: img.py From HUAWEIOCR-2019 with MIT License | 5 votes |
|
def find_contours(mask, method = None):
if method is None:
method = cv2.CHAIN_APPROX_SIMPLE
mask = np.asarray(mask, dtype = np.uint8)
mask = mask.copy()
try:
contours, _ = cv2.findContours(mask, mode = cv2.RETR_CCOMP,
method = method)
except:
_, contours, _ = cv2.findContours(mask, mode = cv2.RETR_CCOMP,
method = method)
return contours
Example #13
| Source File: utils.py From video_analyst with MIT License | 5 votes |
|
def mask_colorize(mask, num_classes, color_map):
"""
transfor one mask to a maske with color
:param mask: mask with shape [h, w]
:param num_classes: number of classes
:param color_map: color map with shape [N, 3]
"""
color_mask = Image.fromarray(mask.astype(np.uint8)).convert('P')
color_mask.putpalette(palette)
raw_mask = np.array(color_mask).astype(np.uint8)
color_mask = cv2.cvtColor(raw_mask, cv2.COLOR_GRAY2BGR)
for c_index in range(num_classes):
instance_mask = (raw_mask == c_index)
if int(cv2.__version__.split(".")[0]) < 4:
_, contour, hier = cv2.findContours(instance_mask.astype(np.uint8),
cv2.RETR_CCOMP,
cv2.CHAIN_APPROX_NONE)
else:
contour, hier = cv2.findContours(instance_mask.astype(np.uint8),
cv2.RETR_CCOMP,
cv2.CHAIN_APPROX_NONE)
if len(contour) > 0:
cv2.drawContours(color_mask, contour, -1, (225, 225, 225), 5)
color_mask[np.where(raw_mask == c_index)] = color_map[c_index]
return color_mask
Example #14
| Source File: img.py From HUAWEIOCR-2019 with MIT License | 5 votes |
|
def find_two_level_contours(mask):
mask = mask.copy()
contours, tree = cv2.findContours(mask, mode = cv2.RETR_CCOMP,
method = cv2.CHAIN_APPROX_SIMPLE)
return contours, tree
Example #15
| Source File: mask_morphology.py From NucleiDetectron with Apache License 2.0 | 5 votes |
|
def opencv_controur_smooth(mask, kernel, k):
if len(mask.shape) == 3:
mask = cv.cvtColor(mask, cv.COLOR_BGR2GRAY)
mask = cv.dilate(mask, kernel, iterations=k)
_, C, h = cv.findContours(mask.copy(), cv.RETR_CCOMP, cv.CHAIN_APPROX_NONE)
seg = [[float(x) for x in contour.flatten()] for contour in C]
seg = [cont for cont in seg if len(cont) > 4] # filter all polygons that are boxes
rles = mask_util.frPyObjects(seg, mask.shape[0], mask.shape[1])
masks = mask_util.decode(rles)
res = []
for idx in range(masks.shape[2]):
res.append(masks[:, :, idx].astype(np.uint8))
return res
Example #16
| Source File: vis.py From NucleiDetectron with Apache License 2.0 | 5 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #17
| Source File: ImagePreprocess.py From GaneratedHandsForReal_TIME with MIT License | 5 votes |
|
def get_largest_contour(org, mask):
_, mask = cv2.threshold(mask, 0, 255, cv2.THRESH_BINARY)
_, contours, hierachy = cv2.findContours(mask, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
if len(contours) == 0:
return None, None, None
max_contour = contours[0]
max_area = cv2.contourArea(max_contour)
for contour in contours:
value = cv2.contourArea(contour)
if max_area < value:
max_contour = contour
max_area = value
x, y, w, h = cv2.boundingRect(max_contour)
h_limit = False
w_limit = False
if h >= 256:
h_limit = True
if w >= 256:
w_limit = True
white = np.zeros((256, 256))
white = cv2.drawContours(white, [max_contour], 0, (255, 255, 255), -1)
white = cv2.drawContours(white, [max_contour], 0, (255, 255, 255), 1)
white = np.asarray(white, np.uint8)
mask = np.bitwise_and(mask, white)
mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
back_real = np.zeros((256, 256, 3))
# org = np.bitwise_and(org, mask)
crop = org[y:y+h,x:x+w]
back_real = org & mask
mask = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY)
back_mask = mask
return crop, back_real, back_mask
Example #18
| Source File: geometry.py From Cytomine-python-client with Apache License 2.0 | 5 votes |
|
def find_components(self):
return self._find_components(cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
Example #19
| Source File: vis.py From CBNet with Apache License 2.0 | 5 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
_, contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #20
| Source File: visualizer.py From detectron2 with Apache License 2.0 | 5 votes |
|
def mask_to_polygons(self, mask):
# cv2.RETR_CCOMP flag retrieves all the contours and arranges them to a 2-level
# hierarchy. External contours (boundary) of the object are placed in hierarchy-1.
# Internal contours (holes) are placed in hierarchy-2.
# cv2.CHAIN_APPROX_NONE flag gets vertices of polygons from contours.
mask = np.ascontiguousarray(mask) # some versions of cv2 does not support incontiguous arr
res = cv2.findContours(mask.astype("uint8"), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
hierarchy = res[-1]
if hierarchy is None: # empty mask
return [], False
has_holes = (hierarchy.reshape(-1, 4)[:, 3] >= 0).sum() > 0
res = res[-2]
res = [x.flatten() for x in res]
res = [x for x in res if len(x) >= 6]
return res, has_holes
Example #21
| Source File: vis.py From Detectron-DA-Faster-RCNN with Apache License 2.0 | 5 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
_, contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #22
| Source File: vis.py From Detectron with Apache License 2.0 | 5 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
contours = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)[-2]
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #23
| Source File: vis.py From Detectron-Cascade-RCNN with Apache License 2.0 | 5 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
_, contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #24
| Source File: visualizer.py From detectron2 with Apache License 2.0 | 5 votes |
|
def mask_to_polygons(self, mask):
# cv2.RETR_CCOMP flag retrieves all the contours and arranges them to a 2-level
# hierarchy. External contours (boundary) of the object are placed in hierarchy-1.
# Internal contours (holes) are placed in hierarchy-2.
# cv2.CHAIN_APPROX_NONE flag gets vertices of polygons from contours.
mask = np.ascontiguousarray(mask) # some versions of cv2 does not support incontiguous arr
res = cv2.findContours(mask.astype("uint8"), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
hierarchy = res[-1]
if hierarchy is None: # empty mask
return [], False
has_holes = (hierarchy.reshape(-1, 4)[:, 3] >= 0).sum() > 0
res = res[-2]
res = [x.flatten() for x in res]
res = [x for x in res if len(x) >= 6]
return res, has_holes
Example #25
| Source File: vis.py From Parsing-R-CNN with MIT License | 5 votes |
|
def vis_uv_temp(img, uv, bbox, show_segms=True):
"""Visualizes a single binary parsing."""
padded_uv = np.zeros((img.shape), dtype=np.float32)
uv_temp = np.array([uv[0], uv[1] * 256, uv[2] * 256]).transpose(1, 2, 0)
y2 = int(bbox[1]) + int(bbox[3] - bbox[1])
x2 = int(bbox[0]) + int(bbox[2] - bbox[0])
padded_uv[int(bbox[1]):y2, int(bbox[0]):x2] = uv_temp
img = img.astype(np.float32)
idx = np.nonzero(padded_uv[:, :, 0])
uv_alpha = cfg.VIS.SHOW_UV.UV_ALPHA
border_color = cfg.VIS.SHOW_UV.BORDER_COLOR
border_thick = cfg.VIS.SHOW_UV.BORDER_THICK
img[idx[0], idx[1], :] *= 1.0 - uv_alpha
img += uv_alpha * padded_uv
if cfg.VIS.SHOW_UV.SHOW_BORDER and not show_segms:
_, contours, _ = cv2.findContours(
padded_uv[:, :, 0].astype(np.uint8).copy(),
cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE
)
cv2.drawContours(img, contours, -1, border_color, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #26
| Source File: postprocess.py From argus-tgs-salt with MIT License | 5 votes |
|
def fix_holes(mask):
_, thresh = cv2.threshold(mask, 127, 255, 0)
_, contour,hier = cv2.findContours(thresh, cv2.RETR_CCOMP,
cv2.CHAIN_APPROX_SIMPLE)
for cnt in contour:
cv2.drawContours(mask, [cnt], 0, 255, -1)
return mask
Example #27
| Source File: vis.py From KL-Loss with Apache License 2.0 | 5 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
_, contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
Example #28
| Source File: process_image.py From RealTime-DigitRecognition with GNU General Public License v3.0 | 5 votes |
|
def get_output_image(path):
img = cv2.imread(path,2)
img_org = cv2.imread(path)
ret,thresh = cv2.threshold(img,127,255,0)
im2,contours,hierarchy = cv2.findContours(thresh, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
for j,cnt in enumerate(contours):
epsilon = 0.01*cv2.arcLength(cnt,True)
approx = cv2.approxPolyDP(cnt,epsilon,True)
hull = cv2.convexHull(cnt)
k = cv2.isContourConvex(cnt)
x,y,w,h = cv2.boundingRect(cnt)
if(hierarchy[0][j][3]!=-1 and w>10 and h>10):
#putting boundary on each digit
cv2.rectangle(img_org,(x,y),(x+w,y+h),(0,255,0),2)
#cropping each image and process
roi = img[y:y+h, x:x+w]
roi = cv2.bitwise_not(roi)
roi = image_refiner(roi)
th,fnl = cv2.threshold(roi,127,255,cv2.THRESH_BINARY)
# getting prediction of cropped image
pred = predict_digit(roi)
print(pred)
# placing label on each digit
(x,y),radius = cv2.minEnclosingCircle(cnt)
img_org = put_label(img_org,pred,x,y)
return img_org
Example #29
| Source File: page_elements2.py From namsel with MIT License | 5 votes |
|
def _contours(self):
# return cv.findContours(self.img_arr.copy(), mode=cv.RETR_CCOMP, method=cv.CHAIN_APPROX_SIMPLE)
# return cv.findContours(self.img_arr.copy(), mode=self._contour_mode , method=cv.CHAIN_APPROX_SIMPLE)
return cv.findContours(self.img_arr.copy(), mode=self._contour_mode,
method=cv.CHAIN_APPROX_SIMPLE)
Example #30
| Source File: vis.py From densepose-video with GNU General Public License v3.0 | 5 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
_, contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick, cv2.LINE_AA)
return img.astype(np.uint8)
