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,