10 examples of 'cv2 resize image' in Python

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def image_resize(image, width = None, height = None, inter = cv2.INTER_AREA):
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    # ref: https://stackoverflow.com/questions/44650888/resize-an-image-without-distortion-opencv
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    # initialize the dimensions of the image to be resized and
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    # grab the image size
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    dim = None
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    (h, w) = image.shape[:2]
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    # if both the width and height are None, then return the
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    # original image
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    if width is None and height is None:
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        return image
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    # check to see if the width is None
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    if width is None:
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        # calculate the ratio of the height and construct the
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        # dimensions
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        r = height / float(h)
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        dim = (int(w * r), height)
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    # otherwise, the height is None
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    else:
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        # calculate the ratio of the width and construct the
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        # dimensions
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        r = width / float(w)
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        dim = (width, int(h * r))
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    # resize the image
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    resized = cv2.resize(image, dim, interpolation = inter)
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    # return the resized image
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    return resized

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def resize_image(image,w,h):
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    image=cv2.resize(image,(w,h))
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    cv2.imwrite(Folder_name+"/Resize-"+str(w)+"*"+str(h)+Extension, image)

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def scale_image(self, image, scale):
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    if self.settings.opencv_or_pil == 'PIL':
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        ow, oh = image.size
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        nw = ow * scale
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        nh = oh * scale
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        return image.resize((int(nw), int(nh)), Image.ANTIALIAS)
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    else:
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        oh, ow, channels = image.shape
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        nw = ow * scale
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        nh = oh * scale
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        # PERF return cv2.resize(image, (int(nw), int(nh)), interpolation=cv2.INTER_NEAREST)
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        return cv2.resize(image, (int(nw), int(nh)), interpolation=cv2.INTER_CUBIC)

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def imresize(img, size, return_scale=False, interpolation='bilinear'):
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    """Resize image to a given size.
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    Args:
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        img (ndarray): The input image.
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        size (tuple): Target (w, h).
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        return_scale (bool): Whether to return `w_scale` and `h_scale`.
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        interpolation (str): Interpolation method, accepted values are
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            "nearest", "bilinear", "bicubic", "area", "lanczos".
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    Returns:
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        tuple or ndarray: (`resized_img`, `w_scale`, `h_scale`) or
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            `resized_img`.
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    """
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    h, w = img.shape[:2]
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    resized_img = cv2.resize(
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        img, size, interpolation=interp_codes[interpolation])
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    if not return_scale:
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        return resized_img
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    else:
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        w_scale = size[0] / w
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        h_scale = size[1] / h
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        return resized_img, w_scale, h_scale

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def __resize_image(self, image):
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    self.input_height = image.shape[0]
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    if self.height is not None:
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        zoom = self.height / float(image.shape[0])
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        width = int(float(image.shape[1]) * zoom) + 1
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        image = cv2.resize(image, (width, self.height), interpolation=cv2.INTER_CUBIC)
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    return image

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def resize_image(self, img, scale):
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    """
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        resize image and transform dimention to [batchsize, channel, height, width]
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    Parameters:
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    ----------
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        img: numpy array , height x width x channel,input image, channels in BGR order here
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        scale: float number, scale factor of resize operation
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    Returns:
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    -------
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        transformed image tensor , 1 x channel x height x width
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    """
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    height, width, channels = img.shape
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    new_height = int(height * scale)     # resized new height
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    new_width = int(width * scale)       # resized new width
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    new_dim = (new_width, new_height)
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    img_resized = cv2.resize(img, new_dim, interpolation=cv2.INTER_LINEAR)      # resized image
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    return img_resized

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def resize_img(img, scale_factor):
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    new_size = (np.floor(np.array(img.shape[0:2]) * scale_factor)).astype(int)
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    new_img = cv2.resize(img, (new_size[1], new_size[0]))
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    # This is scale factor of [height, width] i.e. [y, x]
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    actual_factor = [
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        new_size[0] / float(img.shape[0]), new_size[1] / float(img.shape[1])
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    ]
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    return new_img, actual_factor

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def resizeimg(img, width, height):
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    #img = cv2.imread(path)
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    #img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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    img = cv2.resize(img, (width,height))
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    img = img.astype(float)
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    img = img * (2.0 / 255.0) - 1.0
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    return img

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def resize_image(img, min_side=800, max_side=1333):
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    """ Resize an image such that the size is constrained to min_side and max_side.
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    Args
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        min_side: The image's min side will be equal to min_side after resizing.
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        max_side: If after resizing the image's max side is above max_side, resize until the max side is
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        equal to max_side.
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    Returns
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        A resized image.
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    """
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    (rows, cols, _) = img.shape
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    smallest_side = min(rows, cols)
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    # rescale the image so the smallest side is min_side
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    scale = min_side / smallest_side
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    # check if the largest side is now greater than max_side, which can happen
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    # when images have a large aspect ratio
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    largest_side = max(rows, cols)
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    if largest_side * scale > max_side:
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        scale = max_side / largest_side
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    # resize the image with the computed scale
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    img = cv2.resize(img, None, fx=scale, fy=scale)
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    return img, scale

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def _resize(frame):
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    """Resizing function utilizing OpenCV.
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    Args:
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      frame: A frame from a cv2.video_reader object to process
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    Returns:
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      resized_frame: the frame, resized
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    """
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    resized_frame = cv2.resize(frame,
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                               None,
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                               fx=RESIZE_FACTOR,
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                               fy=RESIZE_FACTOR,
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                               interpolation=cv2.INTER_AREA)
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    return resized_frame