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@@ -53,7 +53,7 @@ def generate_data_svd(data_type, mode):
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# go ahead each scenes
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for id_scene, folder_scene in enumerate(scenes):
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-
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+
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print(folder_scene)
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scene_path = os.path.join(path, folder_scene)
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@@ -78,7 +78,7 @@ def generate_data_svd(data_type, mode):
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index_str = str(index)
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if len(index_str) < 2:
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index_str = "0" + index_str
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-
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+
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current_zone = "zone"+index_str
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zones_folder.append(current_zone)
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@@ -94,7 +94,7 @@ def generate_data_svd(data_type, mode):
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while(current_counter_index <= end_counter_index):
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-
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+
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current_counter_index_str = str(current_counter_index)
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while len(start_index_image) > len(current_counter_index_str):
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@@ -106,19 +106,19 @@ def generate_data_svd(data_type, mode):
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img_blocks = image_processing.divide_in_blocks(current_img, (200, 200))
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for id_block, block in enumerate(img_blocks):
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-
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+
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###########################
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# Metric computation part #
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###########################
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- # get data from mode
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+ # get data from mode
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# Here you can add the way you compute data
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if data_type == 'lab':
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block_file_path = '/tmp/lab_img.png'
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block.save(block_file_path)
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data = image_processing.get_LAB_L_SVD_s(Image.open(block_file_path))
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-
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+
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if data_type == 'mscn_revisited':
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img_mscn_revisited = image_processing.rgb_to_mscn(block)
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@@ -131,7 +131,7 @@ def generate_data_svd(data_type, mode):
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# extract from temp image
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data = metrics.get_SVD_s(img_block)
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-
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+
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if data_type == 'mscn':
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img_gray = np.array(color.rgb2gray(np.asarray(block))*255, 'uint8')
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@@ -144,21 +144,21 @@ def generate_data_svd(data_type, mode):
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if data_type == 'low_bits_4':
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- low_bits_4 = image_processing.rgb_to_grey_low_bits(block)
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+ low_bits_4 = image_processing.rgb_to_LAB_L_low_bits(block)
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# extract from temp image
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data = metrics.get_SVD_s(low_bits_4)
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if data_type == 'low_bits_3':
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- low_bits_3 = image_processing.rgb_to_grey_low_bits(block, 7)
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+ low_bits_3 = image_processing.rgb_to_LAB_L_low_bits(block, 7)
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# extract from temp image
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data = metrics.get_SVD_s(low_bits_3)
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if data_type == 'low_bits_2':
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- low_bits_2 = image_processing.rgb_to_grey_low_bits(block, 3)
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+ low_bits_2 = image_processing.rgb_to_LAB_L_low_bits(block, 3)
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# extract from temp image
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data = metrics.get_SVD_s(low_bits_2)
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@@ -167,22 +167,22 @@ def generate_data_svd(data_type, mode):
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# Data mode part #
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##################
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- # modify data depending mode
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+ # modify data depending mode
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if mode == 'svdne':
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# getting max and min information from min_max_filename
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with open(data_min_max_filename, 'r') as f:
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min_val = float(f.readline())
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max_val = float(f.readline())
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-
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+
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data = image_processing.normalize_arr_with_range(data, min_val, max_val)
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-
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+
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if mode == 'svdn':
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data = image_processing.normalize_arr(data)
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-
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+
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# save min and max found from dataset in order to normalize data using whole data known
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if mode == 'svd':
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-
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+
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current_min = data.min()
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current_max = data.max()
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@@ -192,7 +192,7 @@ def generate_data_svd(data_type, mode):
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if current_max > max_val_found:
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max_val_found = current_max
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- # now write data into current writer
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+ # now write data into current writer
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current_file = svd_output_files[id_block]
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# add of index
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@@ -200,13 +200,13 @@ def generate_data_svd(data_type, mode):
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for val in data:
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current_file.write(str(val) + ";")
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-
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+
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current_file.write('\n')
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start_index_image_int = int(start_index_image)
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print(data_type + "_" + mode + "_" + folder_scene + " - " + "{0:.2f}".format((current_counter_index - start_index_image_int) / (end_counter_index - start_index_image_int)* 100.) + "%")
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current_counter_index += step_counter
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-
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+
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for f in svd_output_files:
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f.close()
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