def generate_histogram(image, image_id, color_space, hist_spec):
"""
Given an image, target operational color space, and the histogram spec from task I,
divide the image into 8x8 image cells, and generate a histogram for each cell,
according to the specification generated by task I.
"""
pixels = image.getdata()
width = image.size[0]
# Convert to target operational color space
pixels = [convert_pixel(pixel, "rgb", color_space) for pixel in pixels]
# Split the image into 8x8 image cells
image_cells = list(get_image_cells(pixels, width, 8, 8))
histogram_output = []
for cell_coord, cell in enumerate(image_cells):
# Dictionary mapping bin id to number of pixels in the bin
bin_counter = dict(zip(range(16), [0] * 16))
for pix_coord, pixel in enumerate(cell):
# Get bin for pixel
bin_counter[bin_pixel(pixel, hist_spec)] += 1
# Output
for color_instance_id, value in bin_counter.items():
histogram_output.append((image_id, cell_coord, color_instance_id, value))
return histogram_output
def angle_histogram_generator(image, image_id, color_space):
'''
given a pil image, the name of that image and a colorspace to work in:
splits the image into 8x8 cells, generates a histogram for each cell.
'''
pixels = image.getdata()
width = image.size[0]
#pixels = [convert_pixel(pixel, color_space, "yuv") for pixel in pixels]
c1,c2,c3 = zip(*pixels)#separate out luminance
if color_space == "RGB" or "rgb":
n1 = 'R'
n2 = 'G'
n3 = 'B'
elif color_space == "YUV" or "yuv":
n1 = 'Y'
n2 = 'U'
n3 = 'V'
else:
n1 = 'H'
n2 = 'S'
n3 = 'V'
histogram_output = []
#for c1:
image_cells = list(get_image_cells(c1, width, 8, 8))
for cell_coord, cell in enumerate(image_cells):
color_instance_id_list, value_list = get_hist_angle_bins(cell)
for i in range (0,16):
histogram_output.append((image_id, cell_coord, n1, i, value_list[i]))
#for c2:
image_cells = list(get_image_cells(c2, width, 8, 8))
for cell_coord, cell in enumerate(image_cells):
color_instance_id_list, value_list = get_hist_angle_bins(cell)
for i in range (0,16):
histogram_output.append((image_id, cell_coord, n2, i, value_list[i]))
#for c3:
image_cells = list(get_image_cells(c3, width, 8, 8))
for cell_coord, cell in enumerate(image_cells):
color_instance_id_list, value_list = get_hist_angle_bins(cell)
for i in range (0,16):
histogram_output.append((image_id, cell_coord, n3, i, value_list[i]))
return histogram_output
def dwt_freq_generator(image, image_id, color_space):
pixels = list(image.getdata())
width = image.size[0]
# Split the image into 8x8 image cells
image_cells = list(get_image_cells(pixels, width, 8, 8))
output = []
for cell_coord, cell in enumerate(image_cells):
channels = zip(*cell)
for channel_id, channel in enumerate(channels):
freq_components = sum([list(x) for x in dwt(list(grouper(width, channel)))], [])
most_significant = freq_components[:16]
for freq_bin, value in enumerate(most_significant):
output.append((image_id, cell_coord, channel_id, freq_bin, value))
return output
