Python cv2.findContours() Examples

The following are 30 code examples of cv2.findContours(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module cv2 , or try the search function .
Example #1
Source Project: vrequest   Author: cilame   File: pycv2.py    License: MIT License 17 votes vote down vote up
def laplacian(filepathname):
    v = cv2.imread(filepathname)
    s = cv2.cvtColor(v, cv2.COLOR_BGR2GRAY)
    s = cv2.Laplacian(s, cv2.CV_16S, ksize=3)
    s = cv2.convertScaleAbs(s)
    cv2.imshow('nier',s)
    return s

    # ret, binary = cv2.threshold(s,40,255,cv2.THRESH_BINARY)
    # contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    # for c in contours:
    #     x,y,w,h = cv2.boundingRect(c)
    #     if w>5 and h>10:
    #         cv2.rectangle(v,(x,y),(x+w,y+h),(155,155,0),1)
    # cv2.imshow('nier2',v)

    # cv2.waitKey()
    # cv2.destroyAllWindows() 
Example #2
Source Project: OpenCV-Computer-Vision-Projects-with-Python   Author: PacktPublishing   File: chapter2.py    License: MIT License 16 votes vote down vote up
def FindHullDefects(self, segment):
        _,contours,hierarchy = cv2.findContours(segment, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

        # find largest area contour
        max_area = -1
        for i in range(len(contours)):
            area = cv2.contourArea(contours[i])
            if area>max_area:
                cnt = contours[i]
                max_area = area

        cnt = cv2.approxPolyDP(cnt,0.01*cv2.arcLength(cnt,True),True)
        hull = cv2.convexHull(cnt, returnPoints=False)
        defects = cv2.convexityDefects(cnt, hull)

        return [cnt,defects] 
Example #3
Source Project: coco-json-converter   Author: hazirbas   File: generate_coco_json.py    License: GNU General Public License v3.0 13 votes vote down vote up
def __get_annotation__(self, mask, image=None):

        _, contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

        segmentation = []
        for contour in contours:
            # Valid polygons have >= 6 coordinates (3 points)
            if contour.size >= 6:
                segmentation.append(contour.flatten().tolist())
        RLEs = cocomask.frPyObjects(segmentation, mask.shape[0], mask.shape[1])
        RLE = cocomask.merge(RLEs)
        # RLE = cocomask.encode(np.asfortranarray(mask))
        area = cocomask.area(RLE)
        [x, y, w, h] = cv2.boundingRect(mask)

        if image is not None:
            image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
            cv2.drawContours(image, contours, -1, (0,255,0), 1)
            cv2.rectangle(image,(x,y),(x+w,y+h), (255,0,0), 2)
            cv2.imshow("", image)
            cv2.waitKey(1)

        return segmentation, [x, y, w, h], area 
Example #4
Source Project: gesture-recognition   Author: Gogul09   File: segment.py    License: MIT License 12 votes vote down vote up
def segment(image, threshold=25):
    global bg
    # find the absolute difference between background and current frame
    diff = cv2.absdiff(bg.astype("uint8"), image)

    # threshold the diff image so that we get the foreground
    thresholded = cv2.threshold(diff, threshold, 255, cv2.THRESH_BINARY)[1]

    # get the contours in the thresholded image
    (_, cnts, _) = cv2.findContours(thresholded.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # return None, if no contours detected
    if len(cnts) == 0:
        return
    else:
        # based on contour area, get the maximum contour which is the hand
        segmented = max(cnts, key=cv2.contourArea)
        return (thresholded, segmented)

#-----------------
# MAIN FUNCTION
#----------------- 
Example #5
Source Project: smashscan   Author: jpnaterer   File: thresholding.py    License: MIT License 11 votes vote down vote up
def contour_filter(self, frame):
        _, contours, _ = cv2.findContours(frame,
            cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

        new_frame = np.zeros(frame.shape, np.uint8)
        for i, contour in enumerate(contours):
            c_area = cv2.contourArea(contour)
            if self.contour_min_area <= c_area <= self.contour_max_area:
                mask = np.zeros(frame.shape, np.uint8)
                cv2.drawContours(mask, contours, i, 255, cv2.FILLED)
                mask = cv2.bitwise_and(frame, mask)
                new_frame = cv2.bitwise_or(new_frame, mask)
        frame = new_frame

        if self.contour_disp_flag:
            frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2BGR)
            cv2.drawContours(frame, contours, -1, (255, 0, 0), 1)

        return frame


    # A number of methods corresponding to the various trackbars available. 
Example #6
Source Project: object-detection   Author: cristianpb   File: motion.py    License: MIT License 10 votes vote down vote up
def prediction(self, image):
        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        image = cv2.GaussianBlur(image, (21, 21), 0)
        if self.avg is None:
            self.avg = image.copy().astype(float)
        cv2.accumulateWeighted(image, self.avg, 0.5)
        frameDelta = cv2.absdiff(image, cv2.convertScaleAbs(self.avg))
        thresh = cv2.threshold(
                frameDelta, DELTA_THRESH, 255,
                cv2.THRESH_BINARY)[1]
        thresh = cv2.dilate(thresh, None, iterations=2)
        cnts = cv2.findContours(
                thresh.copy(), cv2.RETR_EXTERNAL,
                cv2.CHAIN_APPROX_SIMPLE)
        cnts = imutils.grab_contours(cnts)
        self.avg = image.copy().astype(float)
        return cnts 
Example #7
Source Project: gaps   Author: nemanja-m   File: size_detector.py    License: MIT License 9 votes vote down vote up
def _find_size_candidates(self, image):
        binary_image = self._filter_image(image)

        _, contours, _ = cv2.findContours(binary_image,
                                          cv2.RETR_LIST,
                                          cv2.CHAIN_APPROX_SIMPLE)

        size_candidates = []
        for contour in contours:
            bounding_rect = cv2.boundingRect(contour)
            contour_area = cv2.contourArea(contour)
            if self._is_valid_contour(contour_area, bounding_rect):
                candidate = (bounding_rect[2] + bounding_rect[3]) / 2
                size_candidates.append(candidate)

        return size_candidates 
Example #8
Source Project: OpenCV-Python-Tutorial   Author: makelove   File: squares.py    License: MIT License 8 votes vote down vote up
def find_squares(img):
    img = cv2.GaussianBlur(img, (5, 5), 0)
    squares = []
    for gray in cv2.split(img):
        for thrs in xrange(0, 255, 26):
            if thrs == 0:
                bin = cv2.Canny(gray, 0, 50, apertureSize=5)
                bin = cv2.dilate(bin, None)
            else:
                retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY)
            bin, contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
            for cnt in contours:
                cnt_len = cv2.arcLength(cnt, True)
                cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True)
                if len(cnt) == 4 and cv2.contourArea(cnt) > 1000 and cv2.isContourConvex(cnt):
                    cnt = cnt.reshape(-1, 2)
                    max_cos = np.max([angle_cos( cnt[i], cnt[(i+1) % 4], cnt[(i+2) % 4] ) for i in xrange(4)])
                    if max_cos < 0.1:
                        squares.append(cnt)
    return squares 
Example #9
Source Project: vrequest   Author: cilame   File: pycv2.py    License: MIT License 8 votes vote down vote up
def canny(filepathname, left=70, right=140):
    v = cv2.imread(filepathname)
    s = cv2.cvtColor(v, cv2.COLOR_BGR2GRAY)
    s = cv2.Canny(s, left, right)
    cv2.imshow('nier',s)
    return s

    # 圈出最小方矩形框,这里Canny算法后都是白色线条,所以取色范围 127-255 即可。
    # ret, binary = cv2.threshold(s,127,255,cv2.THRESH_BINARY) 
    # contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    # for c in contours:
    #     x,y,w,h = cv2.boundingRect(c)
    #     if w>5 and h>10: # 有约束的画框
    #         cv2.rectangle(v,(x,y),(x+w,y+h),(155,155,0),1)
    # # cv2.drawContours(s,contours,-1,(0,0,255),3) # 画所有框
    # cv2.imshow('nier2',v)

    # cv2.waitKey()
    # cv2.destroyAllWindows() 
Example #10
Source Project: OpenCV-Computer-Vision-Projects-with-Python   Author: PacktPublishing   File: tracking.py    License: MIT License 7 votes vote down vote up
def _append_boxes_from_saliency(self, proto_objects_map, box_all):
        """Adds to the list all bounding boxes found with the saliency map

            A saliency map is used to find objects worth tracking in each
            frame. This information is combined with a mean-shift tracker
            to find objects of relevance that move, and to discard everything
            else.

            :param proto_objects_map: proto-objects map of the current frame
            :param box_all: append bounding boxes from saliency to this list
            :returns: new list of all collected bounding boxes
        """
        # find all bounding boxes in new saliency map
        box_sal = []
        cnt_sal, _ = cv2.findContours(proto_objects_map, 1, 2)
        for cnt in cnt_sal:
            # discard small contours
            if cv2.contourArea(cnt) < self.min_cnt_area:
                continue

            # otherwise add to list of boxes found from saliency map
            box = cv2.boundingRect(cnt)
            box_all.append(box)

        return box_all 
Example #11
Source Project: robosat   Author: mapbox   File: core.py    License: MIT License 7 votes vote down vote up
def contours(mask):
    """Extracts contours and the relationship between them from a binary mask.

    Args:
      mask: the binary mask to find contours in.

    Returns:
      The detected contours as a list of points and the contour hierarchy.

    Note: the hierarchy can be used to re-construct polygons with holes as one entity.
    """

    contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    return contours, hierarchy


# Todo: should work for lines, too, but then needs other epsilon criterion than arc length 
Example #12
Source Project: Res2Net-maskrcnn   Author: Res2Net   File: cv2_util.py    License: MIT License 7 votes vote down vote up
def findContours(*args, **kwargs):
    """
    Wraps cv2.findContours to maintain compatiblity between versions
    3 and 4

    Returns:
        contours, hierarchy
    """
    if cv2.__version__.startswith('4'):
        contours, hierarchy = cv2.findContours(*args, **kwargs)
    elif cv2.__version__.startswith('3'):
        _, contours, hierarchy = cv2.findContours(*args, **kwargs)
    else:
        raise AssertionError(
            'cv2 must be either version 3 or 4 to call this method')

    return contours, hierarchy 
Example #13
Source Project: AerialDetection   Author: dingjiansw101   File: transforms_rbbox.py    License: Apache License 2.0 7 votes vote down vote up
def mask2poly_single(binary_mask):
    """

    :param binary_mask:
    :return:
    """
    try:
        contours, hierarchy = cv2.findContours(binary_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        # contour_lens = np.array(list(map(len, contours)))
        # max_id = contour_lens.argmax()
        # max_contour = contours[max_id]
        max_contour = max(contours, key=len)
        rect = cv2.minAreaRect(max_contour)
        poly = cv2.boxPoints(rect)
        # poly = TuplePoly2Poly(poly)
    except:
        import pdb
        pdb.set_trace()
    return poly 
Example #14
Source Project: Parsing-R-CNN   Author: soeaver   File: vis.py    License: MIT License 7 votes vote down vote up
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 #15
Source Project: Parsing-R-CNN   Author: soeaver   File: vis.py    License: MIT License 7 votes vote down vote up
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 #16
Source Project: Parsing-R-CNN   Author: soeaver   File: segmentation_mask.py    License: MIT License 7 votes vote down vote up
def _findContours(self):
        contours = []
        masks = self.masks.detach().numpy()
        for mask in masks:
            mask = cv2.UMat(mask)
            contour, hierarchy = cv2.findContours(
                mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_L1
            )

            reshaped_contour = []
            for entity in contour:
                assert len(entity.shape) == 3
                assert entity.shape[1] == 1, "Hierarchical contours are not allowed"
                reshaped_contour.append(entity.reshape(-1).tolist())
            contours.append(reshaped_contour)
        return contours 
Example #17
Source Project: R2CNN.pytorch   Author: Xiangyu-CAS   File: cv2_util.py    License: MIT License 7 votes vote down vote up
def findContours(*args, **kwargs):
    """
    Wraps cv2.findContours to maintain compatiblity between versions
    3 and 4

    Returns:
        contours, hierarchy
    """
    if cv2.__version__.startswith('4'):
        contours, hierarchy = cv2.findContours(*args, **kwargs)
    elif cv2.__version__.startswith('3'):
        _, contours, hierarchy = cv2.findContours(*args, **kwargs)
    else:
        raise AssertionError(
            'cv2 must be either version 3 or 4 to call this method')

    return contours, hierarchy 
Example #18
Source Project: PiCamNN   Author: PiSimo   File: picam.py    License: MIT License 7 votes vote down vote up
def movement(mat_1,mat_2):
    mat_1_gray     = cv2.cvtColor(mat_1.copy(),cv2.COLOR_BGR2GRAY)
    mat_1_gray     = cv2.blur(mat_1_gray,(blur1,blur1))
    _,mat_1_gray   = cv2.threshold(mat_1_gray,100,255,0)
    mat_2_gray     = cv2.cvtColor(mat_2.copy(),cv2.COLOR_BGR2GRAY)
    mat_2_gray     = cv2.blur(mat_2_gray,(blur1,blur1))
    _,mat_2_gray   = cv2.threshold(mat_2_gray,100,255,0)
    mat_2_gray     = cv2.bitwise_xor(mat_1_gray,mat_2_gray)
    mat_2_gray     = cv2.blur(mat_2_gray,(blur2,blur2))
    _,mat_2_gray   = cv2.threshold(mat_2_gray,70,255,0)
    mat_2_gray     = cv2.erode(mat_2_gray,np.ones((erodeval,erodeval)))
    mat_2_gray     = cv2.dilate(mat_2_gray,np.ones((4,4)))
    _, contours,__ = cv2.findContours(mat_2_gray,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    if len(contours) > 0:return True #If there were any movements
    return  False                    #if not


#Pedestrian Recognition Thread 
Example #19
Source Project: DEXTR-KerasTensorflow   Author: scaelles   File: helpers.py    License: GNU General Public License v3.0 7 votes vote down vote up
def overlay_masks(im, masks, alpha=0.5):
    colors = np.load(os.path.join(os.path.dirname(__file__), 'pascal_map.npy'))/255.
    
    if isinstance(masks, np.ndarray):
        masks = [masks]

    assert len(colors) >= len(masks), 'Not enough colors'

    ov = im.copy()
    im = im.astype(np.float32)
    total_ma = np.zeros([im.shape[0], im.shape[1]])
    i = 1
    for ma in masks:
        ma = ma.astype(np.bool)
        fg = im * alpha+np.ones(im.shape) * (1 - alpha) * colors[i, :3]   # np.array([0,0,255])/255.0
        i = i + 1
        ov[ma == 1] = fg[ma == 1]
        total_ma += ma

        # [-2:] is s trick to be compatible both with opencv 2 and 3
        contours = cv2.findContours(ma.copy().astype(np.uint8), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)[-2:]
        cv2.drawContours(ov, contours[0], -1, (0.0, 0.0, 0.0), 1)
    ov[total_ma == 0] = im[total_ma == 0]

    return ov 
Example #20
Source Project: SolveSudoku   Author: aakashjhawar   File: SudokuExtractor.py    License: MIT License 7 votes vote down vote up
def find_corners_of_largest_polygon(img):
	"""Finds the 4 extreme corners of the largest contour in the image."""
	opencv_version = cv2.__version__.split('.')[0]
	if opencv_version == '3':
		_, contours, h = cv2.findContours(img.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)  # Find contours
	else:
		contours, h = cv2.findContours(img.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)  # Find contours
	contours = sorted(contours, key=cv2.contourArea, reverse=True)  # Sort by area, descending
	polygon = contours[0]  # Largest image

	# Use of `operator.itemgetter` with `max` and `min` allows us to get the index of the point
	# Each point is an array of 1 coordinate, hence the [0] getter, then [0] or [1] used to get x and y respectively.

	# Bottom-right point has the largest (x + y) value
	# Top-left has point smallest (x + y) value
	# Bottom-left point has smallest (x - y) value
	# Top-right point has largest (x - y) value
	bottom_right, _ = max(enumerate([pt[0][0] + pt[0][1] for pt in polygon]), key=operator.itemgetter(1))
	top_left, _ = min(enumerate([pt[0][0] + pt[0][1] for pt in polygon]), key=operator.itemgetter(1))
	bottom_left, _ = min(enumerate([pt[0][0] - pt[0][1] for pt in polygon]), key=operator.itemgetter(1))
	top_right, _ = max(enumerate([pt[0][0] - pt[0][1] for pt in polygon]), key=operator.itemgetter(1))

	# Return an array of all 4 points using the indices
	# Each point is in its own array of one coordinate
	return [polygon[top_left][0], polygon[top_right][0], polygon[bottom_right][0], polygon[bottom_left][0]] 
Example #21
Source Project: Clothing-Detection   Author: simaiden   File: cv2_util.py    License: GNU General Public License v3.0 7 votes vote down vote up
def findContours(*args, **kwargs):
    """
    Wraps cv2.findContours to maintain compatiblity between versions
    3 and 4

    Returns:
        contours, hierarchy
    """
    if cv2.__version__.startswith('4'):
        contours, hierarchy = cv2.findContours(*args, **kwargs)
    elif cv2.__version__.startswith('3'):
        _, contours, hierarchy = cv2.findContours(*args, **kwargs)
    else:
        raise AssertionError(
            'cv2 must be either version 3 or 4 to call this method')

    return contours, hierarchy 
Example #22
Source Project: ALPR-Indonesia   Author: muchlisinadi   File: DetectChars.py    License: MIT License 6 votes vote down vote up
def findPossibleCharsInPlate(imgGrayscale, imgThresh):
    listOfPossibleChars = []                        # this will be the return value
    contours = []
    imgThreshCopy = imgThresh.copy()

            # find all contours in plate
    contours, npaHierarchy = cv2.findContours(imgThreshCopy, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)

    for contour in contours:                        # for each contour
        possibleChar = PossibleChar.PossibleChar(contour)

        if checkIfPossibleChar(possibleChar):              # if contour is a possible char, note this does not compare to other chars (yet) . . .
            listOfPossibleChars.append(possibleChar)       # add to list of possible chars
        # end if
    # end if

    return listOfPossibleChars
# end function

################################################################################################### 
Example #23
Source Project: EasyPR-python   Author: SunskyF   File: plate_locate.py    License: Apache License 2.0 6 votes vote down vote up
def sobelSecSearchPart(self, bound, refpoint, out):
        bound_threshold = self.sobelOperT(bound, 3, 6, 2)

        tempBoundThread = bound_threshold.copy()
        clearLiuDingOnly(tempBoundThread)

        posLeft, posRight, flag = bFindLeftRightBound(tempBoundThread)
        if flag:
            if posRight != 0 and posLeft != 0 and posLeft < posRight:
                posY = int(bound_threshold.shape[0] * 0.5)
                for i in range(posLeft + int(bound_threshold.shape[0] * 0.1), posRight - 4):
                    bound_threshold[posY, i] = 255
            for i in range(bound_threshold.shape[0]):
                bound_threshold[i, posLeft] = 0
                bound_threshold[i, posRight] = 0

        _, contours, _ = cv2.findContours(bound_threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        for it in contours:
            mr = cv2.minAreaRect(it)
            if self.verifySizes(mr):
                tmp = (mr[0][0] + refpoint[0], mr[0][1] + refpoint[1])
                out.append((tmp, mr[1], mr[2])) 
Example #24
Source Project: EasyPR-python   Author: SunskyF   File: plate_locate.py    License: Apache License 2.0 6 votes vote down vote up
def sobelFrtSearch(self, src):
        out_rects = []

        src_threshold = self.sobelOper(src, self.m_GaussianBlurSize, self.m_MorphSizeWidth, self.m_MorphSizeHeight)
        _, contours, _ = cv2.findContours(src_threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

        for it in contours:
            mr = cv2.minAreaRect(it)

            if self.verifySizes(mr):
                safeBoundRect, flag = self.calcSafeRect(mr, src)
                if not flag:
                    continue
                out_rects.append(safeBoundRect)

        return out_rects 
Example #25
Source Project: EasyPR-python   Author: SunskyF   File: plate_locate.py    License: Apache License 2.0 6 votes vote down vote up
def colorSearch(self, src, color, out_rect):
        """

        :param src:
        :param color:
        :param out_rect: minAreaRect
        :return: binary
        """
        color_morph_width = 10
        color_morph_height = 2

        match_gray = colorMatch(src, color, False)

        _, src_threshold = cv2.threshold(match_gray, 0, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY)

        element = cv2.getStructuringElement(cv2.MORPH_RECT, (color_morph_width, color_morph_height))
        src_threshold = cv2.morphologyEx(src_threshold, cv2.MORPH_CLOSE, element)

        out = src_threshold.copy()

        _, contours, _ = cv2.findContours(src_threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

        for cnt in contours:
            mr = cv2.minAreaRect(cnt)
            if self.verifySizes(mr):
                out_rect.append(mr)

        return out 
Example #26
Source Project: vrequest   Author: cilame   File: pycv2.py    License: MIT License 6 votes vote down vote up
def sobel(filepathname):
    v = cv2.imread(filepathname)
    s = cv2.cvtColor(v,cv2.COLOR_BGR2GRAY)
    x, y = cv2.Sobel(s,cv2.CV_16S,1,0), cv2.Sobel(s,cv2.CV_16S,0,1)
    s = cv2.convertScaleAbs(cv2.subtract(x,y))
    s = cv2.blur(s,(9,9))
    cv2.imshow('nier',s)
    return s

    # ret, binary = cv2.threshold(s,40,255,cv2.THRESH_BINARY)
    # contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    # for c in contours:
    #     x,y,w,h = cv2.boundingRect(c)
    #     if w>5 and h>10:
    #         cv2.rectangle(v,(x,y),(x+w,y+h),(155,155,0),1)
    # cv2.imshow('nier2',v)

    # cv2.waitKey()
    # cv2.destroyAllWindows() 
Example #27
Source Project: CSGNet   Author: Hippogriff   File: Grouping.py    License: MIT License 6 votes vote down vote up
def tightboundingbox(self, image):
        ret, thresh = cv2.threshold(np.array(image, dtype=np.uint8), 0, 255, 0)
        im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
        bb = []
        for c in contours:
            x, y, w, h = cv2.boundingRect(c)
            # +1 is done to encapsulate entire figure
            w += 2
            h += 2
            x -= 1
            y -= 1
            x = np.max([0, x])
            y = np.max([0, y])
            bb.append([y, x, w, h])
        bb = self.nms(bb)
        return bb 
Example #28
Source Project: gesture-recognition   Author: Gogul09   File: recognize.py    License: MIT License 6 votes vote down vote up
def segment(image, threshold=25):
    global bg
    # find the absolute difference between background and current frame
    diff = cv2.absdiff(bg.astype("uint8"), image)

    # threshold the diff image so that we get the foreground
    thresholded = cv2.threshold(diff, threshold, 255, cv2.THRESH_BINARY)[1]

    # get the contours in the thresholded image
    (_, cnts, _) = cv2.findContours(thresholded.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # return None, if no contours detected
    if len(cnts) == 0:
        return
    else:
        # based on contour area, get the maximum contour which is the hand
        segmented = max(cnts, key=cv2.contourArea)
        return (thresholded, segmented)

#--------------------------------------------------------------
# To count the number of fingers in the segmented hand region
#-------------------------------------------------------------- 
Example #29
Source Project: DetNAS   Author: megvii-model   File: cv2_util.py    License: MIT License 6 votes vote down vote up
def findContours(*args, **kwargs):
    """
    Wraps cv2.findContours to maintain compatiblity between versions
    3 and 4

    Returns:
        contours, hierarchy
    """
    if cv2.__version__.startswith('4'):
        contours, hierarchy = cv2.findContours(*args, **kwargs)
    elif cv2.__version__.startswith('3'):
        _, contours, hierarchy = cv2.findContours(*args, **kwargs)
    else:
        raise AssertionError(
            'cv2 must be either version 3 or 4 to call this method')

    return contours, hierarchy 
Example #30
Source Project: DoNotSnap   Author: AVGInnovationLabs   File: RegionOfInterest.py    License: GNU General Public License v3.0 6 votes vote down vote up
def findEllipses(edges):
    contours, _ = cv2.findContours(edges.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
    ellipseMask = np.zeros(edges.shape, dtype=np.uint8)
    contourMask = np.zeros(edges.shape, dtype=np.uint8)

    pi_4 = np.pi * 4

    for i, contour in enumerate(contours):
        if len(contour) < 5:
            continue

        area = cv2.contourArea(contour)
        if area <= 100:  # skip ellipses smaller then 10x10
            continue

        arclen = cv2.arcLength(contour, True)
        circularity = (pi_4 * area) / (arclen * arclen)
        ellipse = cv2.fitEllipse(contour)
        poly = cv2.ellipse2Poly((int(ellipse[0][0]), int(ellipse[0][1])), (int(ellipse[1][0] / 2), int(ellipse[1][1] / 2)), int(ellipse[2]), 0, 360, 5)

        # if contour is circular enough
        if circularity > 0.6:
            cv2.fillPoly(ellipseMask, [poly], 255)
            continue

        # if contour has enough similarity to an ellipse
        similarity = cv2.matchShapes(poly.reshape((poly.shape[0], 1, poly.shape[1])), contour, cv2.cv.CV_CONTOURS_MATCH_I2, 0)
        if similarity <= 0.2:
            cv2.fillPoly(contourMask, [poly], 255)

    return ellipseMask, contourMask