def display_threshld_image(image, threshold_value, max_value, save_image=True):
threshlded_image = processing.get_threshlded_image(image, threshold_value,
max_value)
key_values, color_map_type = get_plot_configs()
plot_title = "Image type"
image_info = [
{
key_values[0]: image,
key_values[1]: "color image",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: threshlded_image,
key_values[1]: "thresholded Image",
key_values[2]: color_map_type["gray"]
},
]
plot_size = get_plot_size(len(image_info))
plot_image(plot_size=plot_size,
plot_title=plot_title,
image_info=image_info,
key_values=key_values)
if save_image:
file_name = get_full_output_path("Color_Image_thresholded.jpg")
cv2.imwrite(file_name, threshlded_image)
def display_resized_image(image, scale_percent, save_image=True):
resized_image = processing.get_resized_image(image, scale_percent)
key_values, color_map_type = get_plot_configs()
plot_title = "resize image by " + str(scale_percent) + " of its size"
image_info = [
{
key_values[0]: image,
key_values[1]: "original image",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: resized_image,
key_values[1]: "resized image",
key_values[2]: color_map_type["color"]
},
]
plot_size = get_plot_size(len(image_info))
plot_image(plot_size=plot_size,
plot_title=plot_title,
image_info=image_info,
key_values=key_values)
if save_image:
file_name = get_full_output_path("Color_Image_resized.jpg")
cv2.imwrite(file_name, cv2.cvtColor(resized_image, cv2.COLOR_BGR2RGB))
def display_tiled_image(image, tile_count, colors, save_image=True):
tiled_image = processing.get_tiled_image(image, tile_count, colors)
key_values, color_map_type = get_plot_configs()
plot_title = "tiled image "
image_info = [
{
key_values[0]: image,
key_values[1]: "original image",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: tiled_image,
key_values[1]: "tiled image",
key_values[2]: color_map_type["color"]
},
]
plot_size = get_plot_size(len(image_info))
plot_image(plot_size=plot_size,
plot_title=plot_title,
image_info=image_info,
key_values=key_values)
if save_image:
file_name = get_full_output_path("Color_Image_modified.jpg")
cv2.imwrite(file_name, cv2.cvtColor(tiled_image, cv2.COLOR_BGR2RGB))
def show(self, image, **args):
if not isinstance(args, dict):
raise AssertionError("args should be provided as a dict")
if len(args) != 2:
raise AssertionError("args is invalid!")
arg_list = list(args.keys())
threshold_value = args[arg_list[0]]
max_value = args[arg_list[1]]
threshlded_image = processing.get_threshlded_image(
image, threshold_value, max_value)
image_info = [
{
self.key_values[0]: image,
self.key_values[1]: "color image",
self.key_values[2]: self.color_map_type["color"]
},
{
self.key_values[0]: threshlded_image,
self.key_values[1]: "thresholded Image",
self.key_values[2]: self.color_map_type["gray"]
},
]
self.plot_image(image_info)
if self.save_image:
file_name = get_full_output_path("Color_Image_thresholded.jpg")
cv2.imwrite(file_name, threshlded_image)
def display_gray_scale_image(image, save_image=True):
grayscale_imag = processing.get_grayscale_image(image)
key_values, color_map_type = get_plot_configs()
plot_title = "Image type"
image_info = [
{
key_values[0]: image,
key_values[1]: "color image",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: grayscale_imag,
key_values[1]: "gray Image",
key_values[2]: color_map_type["gray"]
},
]
plot_size = get_plot_size(len(image_info))
plot_image(plot_size=plot_size,
plot_title=plot_title,
image_info=image_info,
key_values=key_values)
if save_image:
file_name = get_full_output_path("gray_Image.jpg")
cv2.imwrite(file_name, grayscale_imag)
def show(self, image, **args):
if not isinstance(args, dict):
raise AssertionError("args should be provided as a dict")
if len(args) != 2:
raise AssertionError("args is invalid!")
arg_list = list(args.keys())
tile_count = args[arg_list[0]]
colors = args[arg_list[1]]
tiled_image = processing.get_tiled_image(image, tile_count, colors)
image_info = [
{
self.key_values[0]: image,
self.key_values[1]: "original image",
self.key_values[2]: self.color_map_type["color"]
},
{
self.key_values[0]: tiled_image,
self.key_values[1]: "tiled image",
self.key_values[2]: self.color_map_type["color"]
},
]
self.plot_image(image_info)
if self.save_image:
file_name = get_full_output_path("Color_Image_modified.jpg")
cv2.imwrite(file_name, cv2.cvtColor(tiled_image,
cv2.COLOR_BGR2RGB))
def show(self, image, **args):
if not isinstance(args, dict):
raise AssertionError("args should be provided as a dict")
if len(args) != 1:
raise AssertionError("args is invalid!")
scale_percent = next(iter(args.values()))
resized_image = processing.get_resized_image(image, scale_percent)
self.plot_title = "Resized image by " + str(
scale_percent) + " of its size"
image_info = [
{
self.key_values[0]: image,
self.key_values[1]: "original image",
self.key_values[2]: self.color_map_type["color"]
},
{
self.key_values[0]: resized_image,
self.key_values[1]: "resized image",
self.key_values[2]: self.color_map_type["color"]
},
]
self.plot_image(image_info)
if self.save_image:
file_name = get_full_output_path("Color_Image_resized.jpg")
cv2.imwrite(file_name,
cv2.cvtColor(resized_image, cv2.COLOR_BGR2RGB))
def show(self, image, **args):
if not isinstance(args, dict):
raise AssertionError("args should be provided as a dict")
if len(args) != 0:
raise AssertionError("args is invalid!")
grayscale_imag = processing.get_grayscale_image(image)
image_info = [
{
self.key_values[0]: image,
self.key_values[1]: "color image",
self.key_values[2]: self.color_map_type["color"]
},
{
self.key_values[0]: grayscale_imag,
self.key_values[1]: "grayscaled image",
self.key_values[2]: self.color_map_type["gray"]
},
]
self.plot_image(image_info)
if self.save_image:
file_name = get_full_output_path("gray_Image.jpg")
cv2.imwrite(file_name, grayscale_imag)
def display_color_channels(image, save_image=True):
#extract red channel
blue_channel, green_channel, red_channel = get_channels(image)
key_values, color_map_type = get_plot_configs()
plot_title = "color image and its channels"
image_info = [
{
key_values[0]: image,
key_values[1]: "Original image",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: blue_channel,
key_values[1]: "blue channel",
key_values[2]: color_map_type["gray"]
},
{
key_values[0]: green_channel,
key_values[1]: "green channl",
key_values[2]: color_map_type["gray"]
},
{
key_values[0]: red_channel,
key_values[1]: "red channl",
key_values[2]: color_map_type["gray"]
},
]
plot_size = get_plot_size(len(image_info))
plot_image(plot_size=plot_size,
plot_title=plot_title,
image_info=image_info,
key_values=key_values)
if save_image:
file_name = get_full_output_path("blue_channel.jpg")
cv2.imwrite(file_name, blue_channel)
file_name = get_full_output_path("green_channel.jpg")
cv2.imwrite(file_name, green_channel)
file_name = get_full_output_path("red_channel.jpg")
cv2.imwrite(file_name, red_channel)
def show(self, image, **args):
if not isinstance(args, dict):
raise AssertionError("args should be provided as a dict")
if len(args) != 0:
raise AssertionError("args is invalid!")
blue_image, green_image, red_image = ImageInfo.get_image_channels(
image)
image_info = [
{
self.key_values[0]: image,
self.key_values[1]: "Original image",
self.key_values[2]: self.color_map_type["color"]
},
{
self.key_values[0]: blue_image,
self.key_values[1]: "blue channel",
self.key_values[2]: self.color_map_type["color"]
},
{
self.key_values[0]: green_image,
self.key_values[1]: "green channl",
self.key_values[2]: self.color_map_type["color"]
},
{
self.key_values[0]: red_image,
self.key_values[1]: "red channl",
self.key_values[2]: self.color_map_type["color"]
},
]
self.plot_image(image_info)
if self.save_image:
file_name = get_full_output_path("Color_Image_blue.jpg")
cv2.imwrite(file_name, cv2.cvtColor(blue_image, cv2.COLOR_BGR2RGB))
file_name = get_full_output_path("Color_Image_green.jpg")
cv2.imwrite(file_name, cv2.cvtColor(green_image,
cv2.COLOR_BGR2RGB))
file_name = get_full_output_path("Color_Image_red.jpg")
cv2.imwrite(file_name, cv2.cvtColor(red_image, cv2.COLOR_BGR2RGB))
def display_color_image(image, save_image=True):
blue_image, green_image, red_image = get_image_channels(image)
key_values, color_map_type = get_plot_configs()
plot_title = "color image and its channels"
image_info = [
{
key_values[0]: image,
key_values[1]: "Original image",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: blue_image,
key_values[1]: "blue channel",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: green_image,
key_values[1]: "green channl",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: red_image,
key_values[1]: "red channl",
key_values[2]: color_map_type["color"]
},
]
plot_size = get_plot_size(len(image_info))
plot_image(plot_size=plot_size,
plot_title=plot_title,
image_info=image_info,
key_values=key_values)
if save_image:
file_name = get_full_output_path("Color_Image_blue.jpg")
cv2.imwrite(file_name, cv2.cvtColor(blue_image, cv2.COLOR_BGR2RGB))
file_name = get_full_output_path("Color_Image_green.jpg")
cv2.imwrite(file_name, cv2.cvtColor(green_image, cv2.COLOR_BGR2RGB))
file_name = get_full_output_path("Color_Image_red.jpg")
cv2.imwrite(file_name, cv2.cvtColor(red_image, cv2.COLOR_BGR2RGB))
def display_convlution(image, save_image=True):
laplacian = np.array(([0, 1, 0], [1, -4, 1], [0, 1, 0]), dtype="int")
# construct the Sobel x-axis kernel
sobelX = np.array(([-1, 0, 1], [-2, 0, 2], [-1, 0, 1]), dtype="int")
# construct the Sobel y-axis kernel
sobelY = np.array(([-1, -2, -1], [0, 0, 0], [1, 2, 1]), dtype="int")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
conv_x = processing.convolve(gray, sobelX)
post_process_conv_image(conv_x)
conv_y = processing.convolve(gray, sobelY)
post_process_conv_image(conv_y)
conv_laplacian = processing.convolve(gray, laplacian)
post_process_conv_image(conv_laplacian)
# merger X and Y
conv_x_y = conv_x.copy()
conv_x_y = conv_x.__add__(conv_y)
key_values, color_map_type = get_plot_configs()
plot_title = "Edge extraction"
image_info = [
{
key_values[0]: image,
key_values[1]: "Original image",
key_values[2]: color_map_type["color"]
},
{
key_values[0]: gray,
key_values[1]: "grayscale image",
key_values[2]: color_map_type["gray"]
},
{
key_values[0]: conv_x,
key_values[1]: "sobelX image",
key_values[2]: color_map_type["gray"]
},
{
key_values[0]: conv_y,
key_values[1]: "sobelY image",
key_values[2]: color_map_type["gray"]
},
{
key_values[0]: conv_x_y,
key_values[1]: "sobelX_Y image",
key_values[2]: color_map_type["gray"]
},
{
key_values[0]: conv_laplacian,
key_values[1]: "laplacian image",
key_values[2]: color_map_type["gray"]
},
]
plot_size = get_plot_size(len(image_info))
plot_image(plot_size=plot_size,
plot_title=plot_title,
image_info=image_info,
key_values=key_values)
if save_image:
file_name = get_full_output_path("conv_gray_Image.jpg")
cv2.imwrite(file_name, gray)
file_name = get_full_output_path("conv_x.jpg")
cv2.imwrite(file_name, conv_x)
file_name = get_full_output_path("conv_y.jpg")
cv2.imwrite(file_name, conv_y)
file_name = get_full_output_path("conv_x_y.jpg")
cv2.imwrite(file_name, conv_x_y)
file_name = get_full_output_path("conv_laplacian.jpg")
cv2.imwrite(file_name, conv_laplacian)
def show(self, image, **args):
if not isinstance(args, dict):
raise AssertionError("args should be provided as a dict")
if len(args) > 0:
raise AssertionError("args is invalid!")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
conv_x = processing.convolve(gray, self.sobelX)
self.post_process_conv_image(conv_x)
conv_y = processing.convolve(gray, self.sobelY)
self.post_process_conv_image(conv_y)
conv_laplacian = processing.convolve(gray, self.laplacian)
self.post_process_conv_image(conv_laplacian)
# merger X and Y
conv_x_y = conv_x.copy()
conv_x_y = conv_x.__add__(conv_y)
image_info = [{
self.key_values[0]: image,
self.key_values[1]: "Original image",
self.key_values[2]: self.color_map_type["color"]
}, {
self.key_values[0]: gray,
self.key_values[1]: "grayscale image",
self.key_values[2]: self.color_map_type["gray"]
}, {
self.key_values[0]: conv_x,
self.key_values[1]: "sobelX image",
self.key_values[2]: self.color_map_type["gray"]
}, {
self.key_values[0]: conv_y,
self.key_values[1]: "sobelY image",
self.key_values[2]: self.color_map_type["gray"]
}, {
self.key_values[0]: conv_x_y,
self.key_values[1]: "sobelX_Y image",
self.key_values[2]: self.color_map_type["gray"]
}, {
self.key_values[0]: conv_laplacian,
self.key_values[1]: "laplacian image",
self.key_values[2]: self.color_map_type["gray"]
}]
self.plot_image(image_info)
if self.save_image:
file_name = get_full_output_path("conv_gray_Image.jpg")
cv2.imwrite(file_name, gray)
file_name = get_full_output_path("conv_x.jpg")
cv2.imwrite(file_name, conv_x)
file_name = get_full_output_path("conv_y.jpg")
cv2.imwrite(file_name, conv_y)
file_name = get_full_output_path("conv_x_y.jpg")
cv2.imwrite(file_name, conv_x_y)
file_name = get_full_output_path("conv_laplacian.jpg")
cv2.imwrite(file_name, conv_laplacian)
