10 examples of 'opencv resize image' in Python

26
def resize_image(image,w,h):
27
    image=cv2.resize(image,(w,h))
28
    cv2.imwrite(Folder_name+"/Resize-"+str(w)+"*"+str(h)+Extension, image)

141
def resize_image(self, img, scale):
142
    """
143
        resize image and transform dimention to [batchsize, channel, height, width]
144
    Parameters:
145
    ----------
146
        img: numpy array , height x width x channel,input image, channels in BGR order here
147
        scale: float number, scale factor of resize operation
148
    Returns:
149
    -------
150
        transformed image tensor , 1 x channel x height x width
151
    """
152
    height, width, channels = img.shape
153
    new_height = int(height * scale)     # resized new height
154
    new_width = int(width * scale)       # resized new width
155
    new_dim = (new_width, new_height)
156
    img_resized = cv2.resize(img, new_dim, interpolation=cv2.INTER_LINEAR)      # resized image
157
    
158
    return img_resized

38
def image_resize(image, width = None, height = None, inter = cv2.INTER_AREA):
39
    # ref: https://stackoverflow.com/questions/44650888/resize-an-image-without-distortion-opencv
40
41
    # initialize the dimensions of the image to be resized and
42
    # grab the image size
43
    dim = None
44
    (h, w) = image.shape[:2]
45
46
    # if both the width and height are None, then return the
47
    # original image
48
    if width is None and height is None:
49
        return image
50
51
    # check to see if the width is None
52
    if width is None:
53
        # calculate the ratio of the height and construct the
54
        # dimensions
55
        r = height / float(h)
56
        dim = (int(w * r), height)
57
58
    # otherwise, the height is None
59
    else:
60
        # calculate the ratio of the width and construct the
61
        # dimensions
62
        r = width / float(w)
63
        dim = (width, int(h * r))
64
65
    # resize the image
66
    resized = cv2.resize(image, dim, interpolation = inter)
67
68
    # return the resized image
69
    return resized

48
def scale_image(self, image, scale):
49
50
    if self.settings.opencv_or_pil == 'PIL':
51
        ow, oh = image.size
52
        nw = ow * scale
53
        nh = oh * scale
54
        return image.resize((int(nw), int(nh)), Image.ANTIALIAS)
55
56
    else:
57
        oh, ow, channels = image.shape
58
59
        nw = ow * scale
60
        nh = oh * scale
61
62
        # PERF return cv2.resize(image, (int(nw), int(nh)), interpolation=cv2.INTER_NEAREST)
63
        return cv2.resize(image, (int(nw), int(nh)), interpolation=cv2.INTER_CUBIC)

100
def resize(self, width, height):
101
    thumbnail = cv.CreateImage(
102
        (int(round(width, 0)), int(round(height, 0))),
103
        self.image_depth,
104
        self.image_channels
105
    )
106
    cv.Resize(self.image, thumbnail, cv.CV_INTER_AREA)
107
    self.image = thumbnail

103
def __resize_image(self, image):
104
    self.input_height = image.shape[0]
105
    if self.height is not None:
106
        zoom = self.height / float(image.shape[0])
107
        width = int(float(image.shape[1]) * zoom) + 1
108
        image = cv2.resize(image, (width, self.height), interpolation=cv2.INTER_CUBIC)
109
    return image

27
def resizeimg(img, width, height):
28
    #img = cv2.imread(path)
29
    #img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
30
    img = cv2.resize(img, (width,height))
31
    
32
    img = img.astype(float)
33
    img = img * (2.0 / 255.0) - 1.0
34
    return img

29
def imresize(img, size, return_scale=False, interpolation='bilinear'):
30
    """Resize image to a given size.
31
32
    Args:
33
        img (ndarray): The input image.
34
        size (tuple): Target (w, h).
35
        return_scale (bool): Whether to return `w_scale` and `h_scale`.
36
        interpolation (str): Interpolation method, accepted values are
37
            "nearest", "bilinear", "bicubic", "area", "lanczos".
38
39
    Returns:
40
        tuple or ndarray: (`resized_img`, `w_scale`, `h_scale`) or
41
            `resized_img`.
42
    """
43
    h, w = img.shape[:2]
44
    resized_img = cv2.resize(
45
        img, size, interpolation=interp_codes[interpolation])
46
    if not return_scale:
47
        return resized_img
48
    else:
49
        w_scale = size[0] / w
50
        h_scale = size[1] / h
51
        return resized_img, w_scale, h_scale

676
def apply_resize(image, resize_param):
677
  assert isinstance(resize_param.interp_mode, (list, tuple))
678
679
  interp_mode = cv2.INTER_LINEAR
680
  num_interp_mode = len(resize_param.interp_mode)
681
  if num_interp_mode > 0:
682
    probs = [1. / num_interp_mode] * num_interp_mode
683
    cumulative = np.cumsum(probs)
684
    val = random.uniform(0, cumulative[-1])
685
    prob_num = bisect.bisect_left(cumulative, val)
686
    interp_mode = resize_param.interp_mode[prob_num]
687
688
  if resize_param.resize_mode == ResizeParameter.WARP:
689
    return cv2.resize(image, dsize=(resize_param.width, resize_param.height), interpolation=interp_mode)
690
  elif resize_param.resize_mode == ResizeParameter.FIT_LARGE_SIZE_AND_PAD:
691
    return aspect_keeping_resize_and_pad(image, resize_param.width, resize_param.height, resize_param.pad_mode,
692
                                         resize_param.pad_val, interp_mode)
693
  elif resize_param.resize_mode == ResizeParameter.FIT_SMALL_SIZE:
694
    return aspect_keeping_resize_by_small(image, resize_param.width, resize_param.height, interp_mode)
695
  raise Exception()

7
def resize_img(img, scale_factor):
8
    new_size = (np.floor(np.array(img.shape[0:2]) * scale_factor)).astype(int)
9
    new_img = cv2.resize(img, (new_size[1], new_size[0]))
10
    # This is scale factor of [height, width] i.e. [y, x]
11
    actual_factor = [
12
        new_size[0] / float(img.shape[0]), new_size[1] / float(img.shape[1])
13
    ]
14
    return new_img, actual_factor