Commit adf762c2 authored by Bryce Hepner's avatar Bryce Hepner
Browse files

checkpoint, forgot when I was sick

parent de772659

ErrorImageCreator.py

+9 −9
Original line number Original line Diff line number Diff line
@@ -93,26 +93,26 @@ if __name__ == "__main__": 
    list_dic = np.load("second_dic.npy", allow_pickle="TRUE")

    list_dic = np.load("second_dic.npy", allow_pickle="TRUE")

    bins = [21,32,48]

    bins = [21,32,48]

    print(images)

    print(images)

    encoded_string2 = bytes_to_bitstring(read_from_file(images[0][:-5] + "_Compressed.txt"))

    encoded_string2 = bytes_to_bitstring(read_from_file(images[3][:-5] + "_Compressed.txt"))

    original_array, error_array = produce_error_array(encoded_string2, list_dic, bins, False)

    original_array, error_array = produce_error_array(encoded_string2, list_dic, bins, False)

    adjusted_errors = color_adjust(abs(error_array))

    adjusted_errors = color_adjust(abs(error_array))

    original_array_adjusted = color_adjust(original_array)

    original_array_adjusted = color_adjust(original_array)

    # print(adjusted_errors)

    # print(adjusted_errors)

    print(error_array)

    print(error_array)

    plt.subplot(121)

    plt.subplot(131)

    plt.imshow(original_array_adjusted,cmap='gray',vmin = 0, vmax=255)

    plt.imshow(original_array_adjusted,cmap='gray',vmin = 0, vmax=255)

    plt.subplot(122)

    plt.subplot(132)

    plt.imshow(adjusted_errors,cmap = 'gray', vmin = 0, vmax=255)

    plt.imshow(adjusted_errors,cmap = 'gray', vmin = 0, vmax=255)

















    # encoded_string2 = bytes_to_bitstring(read_from_file(images[1][:-5] + "_Compressed.txt"))

    encoded_string2 = bytes_to_bitstring(read_from_file(images[0][:-5] + "_Compressed.txt"))

    # original_array, error_array = produce_error_array(encoded_string2, list_dic, bins, False)

    original_array, error_array = produce_error_array(encoded_string2, list_dic, bins, False)

    # adjusted_errors = color_adjust(abs(error_array))

    adjusted_errors = color_adjust(abs(error_array))

    # original_array_adjusted = color_adjust(original_array)

    original_array_adjusted = color_adjust(original_array)

    # plt.subplot(133)

    plt.subplot(133)

    # plt.imshow(adjusted_errors,cmap = 'gray', vmin = 0, vmax=255)

    plt.imshow(adjusted_errors,cmap = 'gray', vmin = 0, vmax=255)

Remove_Noise.py

+13 −11
Original line number Original line Diff line number Diff line
@@ -9,6 +9,7 @@ def setup_remote_sftpclient(): 
    client.connect("192.168.0.107", username="elphel")

    client.connect("192.168.0.107", username="elphel")

    sftp_client = client.open_sftp()

    sftp_client = client.open_sftp()

    return sftp_client

    return sftp_client



def remove_noise(images, which_sensor):

def remove_noise(images, which_sensor):

    same_sensor_images = []

    same_sensor_images = []

    which_sensor = str(which_sensor)

    which_sensor = str(which_sensor)
@@ -99,14 +100,15 @@ def find_only_in_channel(images, channel_name = "10"): 
                same_sensor_images.append(image_name)

                same_sensor_images.append(image_name)

    return same_sensor_images

    return same_sensor_images

def adjust_to_original(new_image, average_image):

def adjust_to_original(new_image, average_image):

    original_image_min = np.min(new_image)

    # original_image_min = np.min(new_image)

    original_image_max = np.max(new_image)

    # original_image_max = np.max(new_image)

    # average_image = average_image - np.mean(average_image)

    average_image = average_image - np.mean(average_image)

    adjusted_image = new_image - (average_image - gaussian_filter(average_image,sigma=5))

    adjusted_image = new_image - average_image

    # adjusted_image = new_image - (average_image - np.array(Image.fromarray(average_image).convert("L").filter(ImageFilter.GaussianBlur(radius=4))))

    # adjusted_image = new_image + (average_image - gaussian_filter(average_image,sigma=5))

    adjusted_image = adjusted_image - np.min(adjusted_image)

    # adjusted_image = new_image + (average_image - np.array(Image.fromarray(average_image).convert("L").filter(ImageFilter.GaussianBlur(radius=4))))

    adjusted_image = adjusted_image*(original_image_max-original_image_min)/np.max(adjusted_image)

    # adjusted_image = adjusted_image - np.min(adjusted_image)

    adjusted_image = adjusted_image + original_image_min

    # adjusted_image = adjusted_image*(original_image_max-original_image_min)/np.max(adjusted_image)

    # adjusted_image = adjusted_image + original_image_min

    return adjusted_image.astype(np.uint16)

    return adjusted_image.astype(np.uint16)





def color_adjust(visual_array):

def color_adjust(visual_array):
@@ -136,7 +138,7 @@ def create_testable_images(images, selected_channel, quantity_of_images): 
    selected_images = np.array(images)[image_locations]

    selected_images = np.array(images)[image_locations]





    # average_image = np.array(Image.open("Average_On_Channel(" + selected_channel + ").tiff"))

    # average_image = np.array(Image.open("Average_On_Channel(" + selected_channel + ").tiff"))

    images_in_each_direction = 4

    images_in_each_direction = 40

    for i, item in enumerate(selected_images):

    for i, item in enumerate(selected_images):

        if image_locations[i] < images_in_each_direction:

        if image_locations[i] < images_in_each_direction:

            average_image = remote_create_average(images[image_locations[i] - image_locations[i]: image_locations[i] + images_in_each_direction + image_locations[i]], selected_channel)

            average_image = remote_create_average(images[image_locations[i] - image_locations[i]: image_locations[i] + images_in_each_direction + image_locations[i]], selected_channel)
@@ -152,7 +154,7 @@ def create_testable_images(images, selected_channel, quantity_of_images): 
        altered_image = adjust_to_original(image, average_image)

        altered_image = adjust_to_original(image, average_image)

        altered_image = Image.fromarray(altered_image)

        altered_image = Image.fromarray(altered_image)

        

        

        # altered_image.save("averaged_images(" + selected_channel + ")/innerfolder" + item[wherelastslash:])

        altered_image.save("averaged_images(" + selected_channel + ")/innerfolder" + item[wherelastslash:])

        # average_image = Image.fromarray(average_image)

        # average_image = Image.fromarray(average_image)





    sftp_client.close()

    sftp_client.close()
@@ -163,7 +165,7 @@ if __name__ == "__main__": 
    images = remote_image_extractor(scenes)

    images = remote_image_extractor(scenes)

    images = find_only_in_channel(images, "11")

    images = find_only_in_channel(images, "11")

    # average_image = np.array(Image.open("Average_On_Channel(" + "11" + ").tiff"))

    # average_image = np.array(Image.open("Average_On_Channel(" + "11" + ").tiff"))

    create_testable_images(images,"11",10)

    create_testable_images(images,"11",2)

    # plt.imshow(color_adjust(average_image),cmap='gray',vmin = 0, vmax=1)

    # plt.imshow(color_adjust(average_image),cmap='gray',vmin = 0, vmax=1)

    # plt.show()

    # plt.show()

second_dic.npy

+79.8 KiB (227 KiB)

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