def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
# compute hisgoram for each image and add it at the bottom of image_hist
# your code here
for i in range(len(image_list)):
images = np.array(Image.open(image_list[i]))
images = images.astype('double')
if hist_isgray:
image_gray = rgb2gray(images)
hist = histogram_module.get_hist_by_name(image_gray, num_bins,
hist_type)
else:
hist = histogram_module.get_hist_by_name(images, num_bins,
hist_type)
# print(len(hist))
if len(hist) == 2 and len(hist[0]) > 1:
hist = hist[0]
image_hist.append(hist)
return image_hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
# Compute hisgoram for each image and add it at the bottom of image_hist
for image_path in image_list:
image = np.array(Image.open(image_path)).astype('double')
if hist_isgray:
image = rgb2gray(image)
if hist_type == "grayvalue":
hists, _ = histogram_module.get_hist_by_name(
image, num_bins, hist_type)
else:
hists = histogram_module.get_hist_by_name(image, num_bins,
hist_type)
image_hist.append(hists)
return image_hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
for i in range(len(image_list)):
img = (np.array(Image.open(image_list[i]))).astype('double')
if (hist_type == 'dxdy'):
img = rgb2gray(img)
hist = histogram_module.get_hist_by_name(img, num_bins, hist_type)
image_hist.append(hist)
return image_hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
# Compute hisgoram for each image and add it at the bottom of image_hist
for i in image_list:
img = np.array(Image.open(os.path.join(THIS_FOLDER, i)), float)
if hist_isgray:
img = rgb2gray(img)
image_hist.append(histogram_module.get_hist_by_name(img, num_bins, hist_type))
return image_hist
def single_hist_maker(img, hist_type, hist_isgray, num_bins):
# Gray or colored image
if hist_isgray == True:
img = rgb2gray(np.array(Image.open(img)))
else:
img = np.array(Image.open(img))
# Histogram type
hist = histogram_module.get_hist_by_name(np.array(img, float), num_bins,
hist_type)
if hist_type == 'grayvalue':
return hist[0]
else:
return hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
# compute hisgoram for each image and add it at the bottom of image_hist
if hist_isgray:
for name in image_list:
img = Image.open('./' + name)
arr_img = np.array(img, dtype=float)
img_gray = rgb2gray(arr_img)
hist, _ = histogram_module.get_hist_by_name(
img_gray, num_bins, hist_type).tolist()
image_hist.append(hist.tolist())
else:
for name in image_list:
img = Image.open('./' + name)
arr = np.array(img, dtype=float)
hist = histogram_module.get_hist_by_name(arr, num_bins,
hist_type).tolist()
image_hist.append(hist)
return image_hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
# compute histogram for each image and add it at the bottom of image_hist
# your code here
for image_name in image_list:
image = np.array(Image.open(image_name)).astype('double')
if hist_isgray:
image = rgb2gray(image)
image_hist.append(histogram_module.get_hist_by_name(
image, num_bins, hist_type))
return image_hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
# Compute histogram for each image and add it at the bottom of image_hist
# ... (your code here)
for image in image_list:
if hist_isgray:
img_color = np.array(Image.open(image))
img = rgb2gray(img_color.astype('double'))
else:
img = np.array(Image.open(image)).astype('double')
hist = histogram_module.get_hist_by_name(img, num_bins, hist_type)
image_hist.append(hist)
return image_hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
for img in image_list:
img = np.array(Image.open(img)).astype('double')
if hist_isgray:
img = rgb2gray(img)
hist = histogram_module.get_hist_by_name(img, num_bins, hist_type)
if len(hist) == 2:
hist = hist[0]
image_hist.append(hist)
return image_hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
# Compute hisgoram for each image and add it at the bottom of image_hist
for i in range(len(image_list)):
img = np.array(Image.open("./" + image_list[i]))
img = img.astype('double')
if hist_isgray:
img = rgb2gray(img)
hist = histogram_module.get_hist_by_name(img, num_bins, hist_type)
if len(hist) == 2:
hist = hist[0]
image_hist.append(hist)
return image_hist
def compute_histograms(image_list, hist_type, hist_isgray, num_bins):
image_hist = []
# Compute hisgoram for each image and add it at the bottom of image_hist
image_hist = []
for i in range(len(image_list)):
img= np.array(Image.open(image_list[i]))
if histogram_module.is_grayvalue_hist(hist_type)==False:
img= img.astype('double')
elif histogram_module.is_grayvalue_hist(hist_type)==True:
img = rgb2gray(img.astype('double'))
hist = histogram_module.get_hist_by_name(img, num_bins, hist_type)
if len(hist) == 2: # !!!important the normalized histogram(greyvalue name) function returns the bins too, so they are cut at this part
hist = hist[0]
image_hist.append(hist)
return image_hist
img1_color = img1_color.astype('double')
img1_gray = rgb2gray(img1_color)
for img2_file in image_files2:
img2_color = np.array(Image.open(img2_file))
img2_color = img2_color.astype('double')
img2_gray = rgb2gray(img2_color)
D = np.zeros((len(distance_types), len(hist_types)))
for didx in range(len(distance_types)):
for hidx in range(len(hist_types)):
if histogram_module.is_grayvalue_hist(hist_types[hidx]):
hist1 = histogram_module.get_hist_by_name(
img1_gray, num_bins_gray, hist_types[hidx])
hist2 = histogram_module.get_hist_by_name(
img2_gray, num_bins_gray, hist_types[hidx])
else:
hist1 = histogram_module.get_hist_by_name(
img1_color, num_bins_color, hist_types[hidx])
hist2 = histogram_module.get_hist_by_name(
img2_color, num_bins_color, hist_types[hidx])
if len(hist1) == 2:
hist1 = hist1[0]
if len(hist2) == 2:
hist2 = hist2[0]
D[didx,
