Python cv2.COLOR_BGRA2BGR屬性代碼示例

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def get_image_and_mask(img_location, gray_flag):

    # Load image from file with alpha channel (UNCHANGED flag). If an alpha
    # channel does not exist, just return the base image.
    img = cv2.imread(img_location, cv2.IMREAD_UNCHANGED)
    if img.shape[2] <= 3:
        return img, None

    # Create an alpha channel matrix  with values between 0-255. Then
    # threshold the alpha channel to create a binary mask.
    channels = cv2.split(img)
    mask = np.array(channels[3])
    _, mask = cv2.threshold(mask, 250, 255, cv2.THRESH_BINARY)

    # Convert image and mask to grayscale or BGR based on input flag.
    if gray_flag:
        img = cv2.cvtColor(img, cv2.COLOR_BGRA2GRAY)
    else:
        img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
        mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)

    return img, mask


# Resize an image and mask based on an input scale ratio. 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def channel3img(img):
    '''
    If img is 3-channel img(h,w,3) then this is identity funcion.
    If img is grayscale img(h,w) then convert 3-channel img.
    If img is bgra img, then CONVERT to bgr(TODO: warning required!)
    else return None
    '''
    if len(img.shape) == 2:   # if grayscale image, convert.
        return cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
    elif len(img.shape) == 3: 
        _,_,c = img.shape
        if c == 3: # BGR(RGB)
            return img
        elif c == 4: # BGRA(RGBA)
            return cv2.cvtColor(img, cv2.COLOR_BGRA2BGR) 
            #NOTE: warning: no alpha!
    #else: None

#---------------------------------------------------------------------------------
# for segmap 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def grab_image(monitor, resizeTo=None):
    img = cv2.cvtColor(np.array(sct.grab(monitor)), cv2.COLOR_BGRA2BGR)
    if resizeTo is not None:
        return cv2.resize(img, resizeTo)
    return img 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def to_bgr(img):
    if has_alpha(img):
        return cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
    elif is_gray(img):
        return cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
    else:
        return img 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def window_full_shot(self, file_name=None, gray=0):
        """
        窗口截圖
            :param file_name=None: 截圖文件的保存名稱
            :param gray=0: 是否返回灰度圖像，0：返回BGR彩色圖像，其他：返回灰度黑白圖像
            :return: file_name為空則返回RGB數據
        """
        try:
            if (not hasattr(self, 'memdc')):
                self.init_mem()
            if self.client == 0:
                self.memdc.BitBlt((0, 0), (self._client_w, self._client_h), self.srcdc,
                                  (self._border_l, self._border_t), win32con.SRCCOPY)
            else:
                self.memdc.BitBlt((0, -35), (self._client_w, self._client_h), self.srcdc,
                                  (self._border_l, self._border_t), win32con.SRCCOPY)
            if file_name != None:
                self.bmp.SaveBitmapFile(self.memdc, file_name)
                return
            else:
                signedIntsArray = self.bmp.GetBitmapBits(True)
                img = np.fromstring(signedIntsArray, dtype='uint8')
                img.shape = (self._client_h, self._client_w, 4)
                #cv2.imshow("image", cv2.cvtColor(img, cv2.COLOR_BGRA2GRAY))
                # cv2.waitKey(0)
                if gray == 0:
                    return cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
                else:
                    return cv2.cvtColor(img, cv2.COLOR_BGRA2GRAY)
        except Exception:
            self.init_mem()
            logging.warning('window_full_shot執行失敗')
            a = traceback.format_exc()
            logging.warning(a) 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def __annotate_minimap(self, minimap, color_diff, match_val):
        ind_mask_minimap = np.copy(minimap)
        res1 = cv2.bitwise_and(ind_mask_minimap, ind_mask_minimap, mask=self.masks[0])
        ind_area_mask_minimap = np.copy(minimap)
        res2 = cv2.bitwise_and(ind_area_mask_minimap, ind_area_mask_minimap, mask=self.masks[1])

        cv2.putText(minimap, f"{int(color_diff)}", (25, 25), FONT, FONT_SIZE, WHITE())
        cv2.putText(minimap, f"{match_val:.2f}", (25, 60), FONT, FONT_SIZE, WHITE())
        cv2.putText(minimap, f"{self.missed_frames:.2f}", (25, 95), FONT, FONT_SIZE, WHITE())

        minimap = cv2.cvtColor(minimap, cv2.COLOR_BGRA2BGR)
        res1 = cv2.cvtColor(res1, cv2.COLOR_BGRA2BGR)
        res2 = cv2.cvtColor(res2, cv2.COLOR_BGRA2BGR)

        return np.concatenate((res1, res2, minimap), axis=1) 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def spatter(x, severity=1):
    c = [(0.65, 0.3, 4, 0.69, 0.6, 0),
         (0.65, 0.3, 3, 0.68, 0.6, 0),
         (0.65, 0.3, 2, 0.68, 0.5, 0),
         (0.65, 0.3, 1, 0.65, 1.5, 1),
         (0.67, 0.4, 1, 0.65, 1.5, 1)][severity - 1]
    x = np.array(x, dtype=np.float32) / 255.

    liquid_layer = np.random.normal(size=x.shape[:2], loc=c[0], scale=c[1])

    liquid_layer = gaussian(liquid_layer, sigma=c[2])
    liquid_layer[liquid_layer < c[3]] = 0
    if c[5] == 0:
        liquid_layer = (liquid_layer * 255).astype(np.uint8)
        dist = 255 - cv2.Canny(liquid_layer, 50, 150)
        dist = cv2.distanceTransform(dist, cv2.DIST_L2, 5)
        _, dist = cv2.threshold(dist, 20, 20, cv2.THRESH_TRUNC)
        dist = cv2.blur(dist, (3, 3)).astype(np.uint8)
        dist = cv2.equalizeHist(dist)
        ker = np.array([[-2, -1, 0], [-1, 1, 1], [0, 1, 2]])
        dist = cv2.filter2D(dist, cv2.CV_8U, ker)
        dist = cv2.blur(dist, (3, 3)).astype(np.float32)

        m = cv2.cvtColor(liquid_layer * dist, cv2.COLOR_GRAY2BGRA)
        m /= np.max(m, axis=(0, 1))
        m *= c[4]

        # water is pale turqouise
        color = np.concatenate((175 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1])), axis=2)

        color = cv2.cvtColor(color, cv2.COLOR_BGR2BGRA)
        x = cv2.cvtColor(x, cv2.COLOR_BGR2BGRA)

        return cv2.cvtColor(np.clip(x + m * color, 0, 1), cv2.COLOR_BGRA2BGR) * 255
    else:
        m = np.where(liquid_layer > c[3], 1, 0)
        m = gaussian(m.astype(np.float32), sigma=c[4])
        m[m < 0.8] = 0

        # mud brown
        color = np.concatenate((63 / 255. * np.ones_like(x[..., :1]),
                                42 / 255. * np.ones_like(x[..., :1]),
                                20 / 255. * np.ones_like(x[..., :1])), axis=2)

        color *= m[..., np.newaxis]
        x *= (1 - m[..., np.newaxis])

        return np.clip(x + color, 0, 1) * 255 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def spatter(x, severity=1):
    c = [(0.65, 0.3, 4, 0.69, 0.6, 0),
         (0.65, 0.3, 3, 0.68, 0.6, 0),
         (0.65, 0.3, 2, 0.68, 0.5, 0),
         (0.65, 0.3, 1, 0.65, 1.5, 1),
         (0.67, 0.4, 1, 0.65, 1.5, 1)][severity - 1]
    x = np.array(x, dtype=np.float32) / 255.

    liquid_layer = np.random.normal(size=x.shape[:2], loc=c[0], scale=c[1])

    liquid_layer = gaussian(liquid_layer, sigma=c[2])
    liquid_layer[liquid_layer < c[3]] = 0
    if c[5] == 0:
        liquid_layer = (liquid_layer * 255).astype(np.uint8)
        dist = 255 - cv2.Canny(liquid_layer, 50, 150)
        dist = cv2.distanceTransform(dist, cv2.DIST_L2, 5)
        _, dist = cv2.threshold(dist, 20, 20, cv2.THRESH_TRUNC)
        dist = cv2.blur(dist, (3, 3)).astype(np.uint8)
        dist = cv2.equalizeHist(dist)
        #     ker = np.array([[-1,-2,-3],[-2,0,0],[-3,0,1]], dtype=np.float32)
        #     ker -= np.mean(ker)
        ker = np.array([[-2, -1, 0], [-1, 1, 1], [0, 1, 2]])
        dist = cv2.filter2D(dist, cv2.CV_8U, ker)
        dist = cv2.blur(dist, (3, 3)).astype(np.float32)

        m = cv2.cvtColor(liquid_layer * dist, cv2.COLOR_GRAY2BGRA)
        m /= np.max(m, axis=(0, 1))
        m *= c[4]

        # water is pale turqouise
        color = np.concatenate((175 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1])), axis=2)

        color = cv2.cvtColor(color, cv2.COLOR_BGR2BGRA)
        x = cv2.cvtColor(x, cv2.COLOR_BGR2BGRA)

        return cv2.cvtColor(np.clip(x + m * color, 0, 1), cv2.COLOR_BGRA2BGR) * 255
    else:
        m = np.where(liquid_layer > c[3], 1, 0)
        m = gaussian(m.astype(np.float32), sigma=c[4])
        m[m < 0.8] = 0
        #         m = np.abs(m) ** (1/c[4])

        # mud brown
        color = np.concatenate((63 / 255. * np.ones_like(x[..., :1]),
                                42 / 255. * np.ones_like(x[..., :1]),
                                20 / 255. * np.ones_like(x[..., :1])), axis=2)

        color *= m[..., np.newaxis]
        x *= (1 - m[..., np.newaxis])

        return np.clip(x + color, 0, 1) * 255 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def spatter(x, severity=1):
    c = [(0.62,0.1,0.7,0.7,0.5,0),
         (0.65,0.1,0.8,0.7,0.5,0),
         (0.65,0.3,1,0.69,0.5,0),
         (0.65,0.1,0.7,0.69,0.6,1),
         (0.65,0.1,0.5,0.68,0.6,1)][severity - 1]
    x = np.array(x, dtype=np.float32) / 255.

    liquid_layer = np.random.normal(size=x.shape[:2], loc=c[0], scale=c[1])

    liquid_layer = gaussian(liquid_layer, sigma=c[2])
    liquid_layer[liquid_layer < c[3]] = 0
    if c[5] == 0:
        liquid_layer = (liquid_layer * 255).astype(np.uint8)
        dist = 255 - cv2.Canny(liquid_layer, 50, 150)
        dist = cv2.distanceTransform(dist, cv2.DIST_L2, 5)
        _, dist = cv2.threshold(dist, 20, 20, cv2.THRESH_TRUNC)
        dist = cv2.blur(dist, (3, 3)).astype(np.uint8)
        dist = cv2.equalizeHist(dist)
        #     ker = np.array([[-1,-2,-3],[-2,0,0],[-3,0,1]], dtype=np.float32)
        #     ker -= np.mean(ker)
        ker = np.array([[-2, -1, 0], [-1, 1, 1], [0, 1, 2]])
        dist = cv2.filter2D(dist, cv2.CV_8U, ker)
        dist = cv2.blur(dist, (3, 3)).astype(np.float32)

        m = cv2.cvtColor(liquid_layer * dist, cv2.COLOR_GRAY2BGRA)
        m /= np.max(m, axis=(0, 1))
        m *= c[4]

        # water is pale turqouise
        color = np.concatenate((175 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1])), axis=2)

        color = cv2.cvtColor(color, cv2.COLOR_BGR2BGRA)
        x = cv2.cvtColor(x, cv2.COLOR_BGR2BGRA)

        return cv2.cvtColor(np.clip(x + m * color, 0, 1), cv2.COLOR_BGRA2BGR) * 255
    else:
        m = np.where(liquid_layer > c[3], 1, 0)
        m = gaussian(m.astype(np.float32), sigma=c[4])
        m[m < 0.8] = 0
        #         m = np.abs(m) ** (1/c[4])

        # mud brown
        color = np.concatenate((63 / 255. * np.ones_like(x[..., :1]),
                                42 / 255. * np.ones_like(x[..., :1]),
                                20 / 255. * np.ones_like(x[..., :1])), axis=2)

        color *= m[..., np.newaxis]
        x *= (1 - m[..., np.newaxis])

        return np.clip(x + color, 0, 1) * 255 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def spatter(x, severity=1):
    c = [(0.62,0.1,0.7,0.7,0.6,0),
         (0.65,0.1,0.8,0.7,0.6,0),
         (0.65,0.3,1,0.69,0.6,0),
         (0.65,0.1,0.7,0.68,0.6,1),
         (0.65,0.1,0.5,0.67,0.6,1)][severity - 1]
    x = np.array(x, dtype=np.float32) / 255.

    liquid_layer = np.random.normal(size=x.shape[:2], loc=c[0], scale=c[1])

    liquid_layer = gaussian(liquid_layer, sigma=c[2])
    liquid_layer[liquid_layer < c[3]] = 0
    if c[5] == 0:
        liquid_layer = (liquid_layer * 255).astype(np.uint8)
        dist = 255 - cv2.Canny(liquid_layer, 50, 150)
        dist = cv2.distanceTransform(dist, cv2.DIST_L2, 5)
        _, dist = cv2.threshold(dist, 20, 20, cv2.THRESH_TRUNC)
        dist = cv2.blur(dist, (3, 3)).astype(np.uint8)
        dist = cv2.equalizeHist(dist)
        #     ker = np.array([[-1,-2,-3],[-2,0,0],[-3,0,1]], dtype=np.float32)
        #     ker -= np.mean(ker)
        ker = np.array([[-2, -1, 0], [-1, 1, 1], [0, 1, 2]])
        dist = cv2.filter2D(dist, cv2.CV_8U, ker)
        dist = cv2.blur(dist, (3, 3)).astype(np.float32)

        m = cv2.cvtColor(liquid_layer * dist, cv2.COLOR_GRAY2BGRA)
        m /= np.max(m, axis=(0, 1))
        m *= c[4]

        # water is pale turqouise
        color = np.concatenate((175 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1])), axis=2)

        color = cv2.cvtColor(color, cv2.COLOR_BGR2BGRA)
        x = cv2.cvtColor(x, cv2.COLOR_BGR2BGRA)

        return cv2.cvtColor(np.clip(x + m * color, 0, 1), cv2.COLOR_BGRA2BGR) * 255
    else:
        m = np.where(liquid_layer > c[3], 1, 0)
        m = gaussian(m.astype(np.float32), sigma=c[4])
        m[m < 0.8] = 0
        #         m = np.abs(m) ** (1/c[4])

        # mud brown
        color = np.concatenate((63 / 255. * np.ones_like(x[..., :1]),
                                42 / 255. * np.ones_like(x[..., :1]),
                                20 / 255. * np.ones_like(x[..., :1])), axis=2)

        color *= m[..., np.newaxis]
        x *= (1 - m[..., np.newaxis])

        return np.clip(x + color, 0, 1) * 255 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def spatter(x, severity=1):
    c = [(0.65,0.3,4,0.69,0.9,0),
         (0.65,0.3,3.5,0.68,0.9,0),
         (0.65,0.3,3,0.68,0.8,0),
         (0.65,0.3,1.2,0.65,1.8,1),
         (0.67,0.4,1.2,0.65,1.8,1)][severity - 1]
    x = np.array(x, dtype=np.float32) / 255.

    liquid_layer = np.random.normal(size=x.shape[:2], loc=c[0], scale=c[1])

    liquid_layer = gaussian(liquid_layer, sigma=c[2])
    liquid_layer[liquid_layer < c[3]] = 0
    if c[5] == 0:
        liquid_layer = (liquid_layer * 255).astype(np.uint8)
        dist = 255 - cv2.Canny(liquid_layer, 50, 150)
        dist = cv2.distanceTransform(dist, cv2.DIST_L2, 5)
        _, dist = cv2.threshold(dist, 20, 20, cv2.THRESH_TRUNC)
        dist = cv2.blur(dist, (3, 3)).astype(np.uint8)
        dist = cv2.equalizeHist(dist)
        #     ker = np.array([[-1,-2,-3],[-2,0,0],[-3,0,1]], dtype=np.float32)
        #     ker -= np.mean(ker)
        ker = np.array([[-2, -1, 0], [-1, 1, 1], [0, 1, 2]])
        dist = cv2.filter2D(dist, cv2.CV_8U, ker)
        dist = cv2.blur(dist, (3, 3)).astype(np.float32)

        m = cv2.cvtColor(liquid_layer * dist, cv2.COLOR_GRAY2BGRA)
        m /= np.max(m, axis=(0, 1))
        m *= c[4]

        # water is pale turqouise
        color = np.concatenate((175 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1]),
                                238 / 255. * np.ones_like(m[..., :1])), axis=2)

        color = cv2.cvtColor(color, cv2.COLOR_BGR2BGRA)
        x = cv2.cvtColor(x, cv2.COLOR_BGR2BGRA)

        return cv2.cvtColor(np.clip(x + m * color, 0, 1), cv2.COLOR_BGRA2BGR) * 255
    else:
        m = np.where(liquid_layer > c[3], 1, 0)
        m = gaussian(m.astype(np.float32), sigma=c[4])
        m[m < 0.8] = 0
        #         m = np.abs(m) ** (1/c[4])

        # mud brown
        color = np.concatenate((63 / 255. * np.ones_like(x[..., :1]),
                                42 / 255. * np.ones_like(x[..., :1]),
                                20 / 255. * np.ones_like(x[..., :1])), axis=2)

        color *= m[..., np.newaxis]
        x *= (1 - m[..., np.newaxis])

        return np.clip(x + color, 0, 1) * 255 

# 需要導入模塊: import cv2 [as 別名]
# 或者: from cv2 import COLOR_BGRA2BGR [as 別名]
def window_part_shot(self, pos1, pos2, file_name=None, gray=0):
        """
        窗口區域截圖
            :param pos1: (x,y) 截圖區域的左上角坐標
            :param pos2: (x,y) 截圖區域的右下角坐標
            :param file_name=None: 截圖文件的保存路徑
            :param gray=0: 是否返回灰度圖像，0：返回BGR彩色圖像，其他：返回灰度黑白圖像
            :return: file_name為空則返回RGB數據
        """
        w = pos2[0]-pos1[0]
        h = pos2[1]-pos1[1]
        hwindc = win32gui.GetWindowDC(self.hwnd)
        srcdc = win32ui.CreateDCFromHandle(hwindc)
        memdc = srcdc.CreateCompatibleDC()
        bmp = win32ui.CreateBitmap()
        bmp.CreateCompatibleBitmap(srcdc, w, h)
        memdc.SelectObject(bmp)
        if self.client == 0:
            memdc.BitBlt((0, 0), (w, h), srcdc,
                         (pos1[0]+self._border_l, pos1[1]+self._border_t), win32con.SRCCOPY)
        else:
            memdc.BitBlt((0, -35), (w, h), srcdc,
                         (pos1[0]+self._border_l, pos1[1]+self._border_t), win32con.SRCCOPY)
        if file_name != None:
            bmp.SaveBitmapFile(memdc, file_name)
            srcdc.DeleteDC()
            memdc.DeleteDC()
            win32gui.ReleaseDC(self.hwnd, hwindc)
            win32gui.DeleteObject(bmp.GetHandle())
            return
        else:
            signedIntsArray = bmp.GetBitmapBits(True)
            img = np.fromstring(signedIntsArray, dtype='uint8')
            img.shape = (h, w, 4)
            srcdc.DeleteDC()
            memdc.DeleteDC()
            win32gui.ReleaseDC(self.hwnd, hwindc)
            win32gui.DeleteObject(bmp.GetHandle())
            #cv2.imshow("image", cv2.cvtColor(img, cv2.COLOR_BGRA2BGR))
            # cv2.waitKey(0)
            if gray == 0:
                return cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
            else:
                return cv2.cvtColor(img, cv2.COLOR_BGRA2GRAY)