From 72646becd11e3ed287ea1aa0b2f662789fbc540c Mon Sep 17 00:00:00 2001 From: iperov Date: Thu, 24 Jan 2019 21:32:07 +0400 Subject: [PATCH] forcing all tqdm's to ascii in order to work properly on Chinese windows --- mainscripts/Converter.py | 2 +- mainscripts/Extractor.py | 1 - mainscripts/Sorter.py | 36 ++++++++++++++++++------------------ samples/SampleLoader.py | 8 ++++---- utils/SubprocessorBase.py | 2 +- 5 files changed, 24 insertions(+), 25 deletions(-) diff --git a/mainscripts/Converter.py b/mainscripts/Converter.py index 80b4738..74d37c1 100644 --- a/mainscripts/Converter.py +++ b/mainscripts/Converter.py @@ -259,7 +259,7 @@ def main (input_dir, output_dir, model_dir, model_name, aligned_dir=None, **in_o alignments = {} aligned_path_image_paths = Path_utils.get_image_paths(aligned_path) - for filename in tqdm(aligned_path_image_paths, desc= "Collecting alignments" ): + for filename in tqdm(aligned_path_image_paths, desc="Collecting alignments", ascii=True ): dflpng = DFLPNG.load( str(filename), print_on_no_embedded_data=True ) if dflpng is None: continue diff --git a/mainscripts/Extractor.py b/mainscripts/Extractor.py index a9eb941..23e4b4e 100644 --- a/mainscripts/Extractor.py +++ b/mainscripts/Extractor.py @@ -3,7 +3,6 @@ import os import sys import time import multiprocessing -from tqdm import tqdm from pathlib import Path import numpy as np import cv2 diff --git a/mainscripts/Sorter.py b/mainscripts/Sorter.py index e0826b2..f723704 100644 --- a/mainscripts/Sorter.py +++ b/mainscripts/Sorter.py @@ -131,14 +131,14 @@ def sort_by_blur(input_path): def sort_by_brightness(input_path): print ("Sorting by brightness...") - img_list = [ [x, np.mean ( cv2.cvtColor(cv2.imread(x), cv2.COLOR_BGR2HSV)[...,2].flatten() )] for x in tqdm( Path_utils.get_image_paths(input_path), desc="Loading") ] + img_list = [ [x, np.mean ( cv2.cvtColor(cv2.imread(x), cv2.COLOR_BGR2HSV)[...,2].flatten() )] for x in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True) ] print ("Sorting...") img_list = sorted(img_list, key=operator.itemgetter(1), reverse=True) return img_list def sort_by_hue(input_path): print ("Sorting by hue...") - img_list = [ [x, np.mean ( cv2.cvtColor(cv2.imread(x), cv2.COLOR_BGR2HSV)[...,0].flatten() )] for x in tqdm( Path_utils.get_image_paths(input_path), desc="Loading") ] + img_list = [ [x, np.mean ( cv2.cvtColor(cv2.imread(x), cv2.COLOR_BGR2HSV)[...,0].flatten() )] for x in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True) ] print ("Sorting...") img_list = sorted(img_list, key=operator.itemgetter(1), reverse=True) return img_list @@ -148,7 +148,7 @@ def sort_by_face(input_path): print ("Sorting by face similarity...") img_list = [] - for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading"): + for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True): filepath = Path(filepath) if filepath.suffix != '.png': @@ -163,7 +163,7 @@ def sort_by_face(input_path): img_list_len = len(img_list) - for i in tqdm ( range(0, img_list_len-1), desc="Sorting"): + for i in tqdm ( range(0, img_list_len-1), desc="Sorting", ascii=True): min_score = float("inf") j_min_score = i+1 for j in range(i+1,len(img_list)): @@ -184,7 +184,7 @@ def sort_by_face_dissim(input_path): print ("Sorting by face dissimilarity...") img_list = [] - for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading"): + for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True): filepath = Path(filepath) if filepath.suffix != '.png': @@ -198,7 +198,7 @@ def sort_by_face_dissim(input_path): img_list.append( [str(filepath), dflpng.get_landmarks(), 0 ] ) img_list_len = len(img_list) - for i in tqdm( range(0, img_list_len-1), desc="Sorting"): + for i in tqdm( range(0, img_list_len-1), desc="Sorting", ascii=True): score_total = 0 for j in range(i+1,len(img_list)): if i == j: @@ -217,7 +217,7 @@ def sort_by_face_dissim(input_path): def sort_by_face_yaw(input_path): print ("Sorting by face yaw...") img_list = [] - for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading"): + for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True): filepath = Path(filepath) if filepath.suffix != '.png': @@ -436,7 +436,7 @@ def sort_by_hist_dissim(input_path): print ("Sorting by histogram dissimilarity...") img_list = [] - for filename_path in tqdm( Path_utils.get_image_paths(input_path), desc="Loading"): + for filename_path in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True): image = cv2.imread(filename_path) dflpng = DFLPNG.load( str(filename_path) ) @@ -563,7 +563,7 @@ def sort_final(input_path): grads_space = np.linspace (-255,255,grads) yaws_sample_list = [None]*grads - for g in tqdm ( range(grads), desc="Sort by yaw" ): + for g in tqdm ( range(grads), desc="Sort by yaw", ascii=True ): yaw = grads_space[g] next_yaw = grads_space[g+1] if g < grads-1 else yaw @@ -578,7 +578,7 @@ def sort_final(input_path): yaws_sample_list[g] = yaw_samples total_lack = 0 - for g in tqdm ( range (grads), desc="" ): + for g in tqdm ( range (grads), desc="", ascii=True ): img_list = yaws_sample_list[g] img_list_len = len(img_list) if img_list is not None else 0 @@ -588,7 +588,7 @@ def sort_final(input_path): imgs_per_grad += total_lack // grads sharpned_imgs_per_grad = imgs_per_grad*10 - for g in tqdm ( range (grads), desc="Sort by blur" ): + for g in tqdm ( range (grads), desc="Sort by blur", ascii=True ): img_list = yaws_sample_list[g] if img_list is None: continue @@ -605,7 +605,7 @@ def sort_final(input_path): yaws_sample_list[g] = img_list - for g in tqdm ( range (grads), desc="Sort by hist" ): + for g in tqdm ( range (grads), desc="Sort by hist", ascii=True ): img_list = yaws_sample_list[g] if img_list is None: continue @@ -620,7 +620,7 @@ def sort_final(input_path): yaws_sample_list[g] = sorted(img_list, key=operator.itemgetter(3), reverse=True) - for g in tqdm ( range (grads), desc="Fetching best" ): + for g in tqdm ( range (grads), desc="Fetching best", ascii=True ): img_list = yaws_sample_list[g] if img_list is None: continue @@ -634,7 +634,7 @@ def sort_by_black(input_path): print ("Sorting by amount of black pixels...") img_list = [] - for x in tqdm( Path_utils.get_image_paths(input_path), desc="Loading"): + for x in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True): img = cv2.imread(x) img_list.append ([x, img[(img == 0)].size ]) @@ -654,7 +654,7 @@ def final_process(input_path, img_list, trash_img_list): for filename in Path_utils.get_image_paths(trash_path): Path(filename).unlink() - for i in tqdm( range(len(trash_img_list)), desc="Moving trash" , leave=False): + for i in tqdm( range(len(trash_img_list)), desc="Moving trash" , leave=False, ascii=True): src = Path (trash_img_list[i][0]) dst = trash_path / src.name try: @@ -664,7 +664,7 @@ def final_process(input_path, img_list, trash_img_list): print ("") - for i in tqdm( range(len(img_list)), desc="Renaming" , leave=False): + for i in tqdm( range(len(img_list)), desc="Renaming" , leave=False, ascii=True): src = Path (img_list[i][0]) dst = input_path / ('%.5d_%s' % (i, src.name )) try: @@ -672,7 +672,7 @@ def final_process(input_path, img_list, trash_img_list): except: print ('fail to rename %s' % (src.name) ) - for i in tqdm( range(len(img_list)) , desc="Renaming" ): + for i in tqdm( range(len(img_list)) , desc="Renaming", ascii=True ): src = Path (img_list[i][0]) src = input_path / ('%.5d_%s' % (i, src.name)) @@ -686,7 +686,7 @@ def sort_by_origname(input_path): print ("Sort by original filename...") img_list = [] - for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading"): + for filepath in tqdm( Path_utils.get_image_paths(input_path), desc="Loading", ascii=True): filepath = Path(filepath) if filepath.suffix != '.png': diff --git a/samples/SampleLoader.py b/samples/SampleLoader.py index 9d0ea14..4841d4c 100644 --- a/samples/SampleLoader.py +++ b/samples/SampleLoader.py @@ -27,7 +27,7 @@ class SampleLoader: if sample_type == SampleType.IMAGE: if datas[sample_type] is None: - datas[sample_type] = [ Sample(filename=filename) for filename in tqdm( Path_utils.get_image_paths(samples_path), desc="Loading" ) ] + datas[sample_type] = [ Sample(filename=filename) for filename in tqdm( Path_utils.get_image_paths(samples_path), desc="Loading", ascii=True ) ] elif sample_type == SampleType.FACE: if datas[sample_type] is None: @@ -53,7 +53,7 @@ class SampleLoader: def upgradeToFaceSamples ( samples ): sample_list = [] - for s in tqdm( samples, desc="Loading" ): + for s in tqdm( samples, desc="Loading", ascii=True ): s_filename_path = Path(s.filename) if s_filename_path.suffix != '.png': @@ -78,7 +78,7 @@ class SampleLoader: yaw_samples_len = len(yaw_samples) sample_list = [] - for i in tqdm( range(yaw_samples_len), desc="Sorting" ): + for i in tqdm( range(yaw_samples_len), desc="Sorting", ascii=True ): if yaw_samples[i] is not None: for s in yaw_samples[i]: s_t = [] @@ -114,7 +114,7 @@ class SampleLoader: yaws_sample_list = [None]*gradations - for i in tqdm( range(0, gradations), desc="Sorting" ): + for i in tqdm( range(0, gradations), desc="Sorting", ascii=True ): yaw = lowest_yaw + i*diff_rot_per_grad next_yaw = lowest_yaw + (i+1)*diff_rot_per_grad diff --git a/utils/SubprocessorBase.py b/utils/SubprocessorBase.py index 94b687a..3a85616 100644 --- a/utils/SubprocessorBase.py +++ b/utils/SubprocessorBase.py @@ -134,7 +134,7 @@ class SubprocessorBase(object): print ( self.get_no_process_started_message() ) return None - self.progress_bar = tqdm( total=self.onHostGetProgressBarLen(), desc=self.onHostGetProgressBarDesc() ) + self.progress_bar = tqdm( total=self.onHostGetProgressBarLen(), desc=self.onHostGetProgressBarDesc(), ascii=True ) self.onHostClientsInitialized() try: