Refactoring

monoloco/prep/__init__.py

@@ -1,3 +1,3 @@
 
 from .preprocess_kitti import parse_ground_truth, factory_file
-from .casr_preprocess import create_dic
+from .preprocess_casr import create_dic

monoloco/prep/casr_preprocess.py

@@ -1,100 +0,0 @@
-import pickle
-import re
-import json
-import os
-import glob
-import datetime
-import numpy as np
-import torch
-
-from .. import __version__
-from ..network.process import preprocess_monoloco
-
-gt_path = '/scratch/izar/beauvill/casr/data/annotations/casr_annotation.pickle'
-res_path = '/scratch/izar/beauvill/casr/res_extended/casr*'
-
-def bb_intersection_over_union(boxA, boxB):
-    xA = max(boxA[0], boxB[0])
-    yA = max(boxA[1], boxB[1])
-    xB = min(boxA[2], boxB[2])
-    yB = min(boxA[3], boxB[3])
-    interArea = max(0, xB - xA + 1) * max(0, yB - yA + 1)
-    boxAArea = (boxA[2] - boxA[0] + 1) * (boxA[3] - boxA[1] + 1)
-    boxBArea = (boxB[2] - boxB[0] + 1) * (boxB[3] - boxB[1] + 1)
-    iou = interArea / float(boxAArea + boxBArea - interArea)
-    return iou
-
-def match_bboxes(bbox_gt, bbox_pred):
-    n_true = bbox_gt.shape[0]
-    n_pred = bbox_pred.shape[0]
-
-    iou_matrix = np.zeros((n_true, n_pred))
-    for i in range(n_true):
-        for j in range(n_pred):
-            iou_matrix[i, j] = bb_intersection_over_union(bbox_gt[i,:], bbox_pred[j,:])
-
-    return np.argmax(iou_matrix)
-
-def standard_bbox(bbox):
-    return [bbox[0], bbox[1], bbox[0]+bbox[2], bbox[1]+bbox[3]]
-
-def load_gt():
-    return pickle.load(open(gt_path, 'rb'), encoding='latin1')
-
-def load_res():
-    mono = []
-    for folder in sorted(glob.glob(res_path), key=lambda x:float(re.findall(r"(\d+)",x)[0])):
-        data_list = []
-        for file in sorted(os.listdir(folder), key=lambda x:float(re.findall(r"(\d+)",x)[0])):
-            if 'json' in file:
-                json_path = os.path.join(folder, file)
-                json_data = json.load(open(json_path))
-                json_data['filename'] = json_path
-                data_list.append(json_data)
-        mono.append(data_list)
-    return mono
-
-def create_dic(std=False):
-    gt=load_gt()
-    res=load_res()
-    dic_jo = {
-        'train': dict(X=[], Y=[], names=[], kps=[]),
-        'val': dict(X=[], Y=[], names=[], kps=[]),
-        'version': __version__,
-    }
-    split = ['3', '4']
-    if std:
-        wrong = [6, 8, 9, 10, 11, 12, 14, 21, 40, 43, 55, 70, 76, 92, 109,
-                 110, 112, 113, 121, 123, 124, 127, 128, 134, 136, 139, 165, 173]
-        mode = 'std'
-    else:
-        wrong = []
-        mode = ''
-    for i in [x for x in range(len(res[:])) if x not in wrong]:
-        for j in [x for x in range(len(res[i][:])) if 'boxes' in res[i][x]]:
-            folder = gt[i][j]['video_folder']
-
-            phase = 'val'
-            if folder[7] in split:
-                phase = 'train'
-
-            gt_box = gt[i][j]['bbox_gt']
-
-            good_idx = match_bboxes(np.array([standard_bbox(gt_box)]), np.array(res[i][j]['boxes'])[:,:4])
-
-            keypoints = [res[i][j]['uv_kps'][good_idx]]
-
-            gt_turn = gt[i][j]['left_or_right']
-            if std and gt_turn == 3:
-                gt_turn = 2
-            inp = preprocess_monoloco(keypoints, torch.eye(3)).view(-1).tolist()
-            dic_jo[phase]['kps'].append(keypoints)
-            dic_jo[phase]['X'].append(inp)
-            dic_jo[phase]['Y'].append(gt_turn)
-            dic_jo[phase]['names'].append(folder+"_frame{}".format(j))
-
-    now_time = datetime.datetime.now().strftime("%Y%m%d-%H%M")[2:]
-    with open("/home/beauvill/joints-casr-" + mode + "-right-" +
-              split[0] + split[1] + "-" + now_time + ".json", 'w') as file:
-        json.dump(dic_jo, file)
-    return dic_jo

monoloco/run.py

@@ -82,6 +82,7 @@ def cli():
                              help='datasets to preprocess: nuscenes, nuscenes_teaser, nuscenes_mini, kitti',
                              default='kitti')
     prep_parser.add_argument('--dir_nuscenes', help='directory of nuscenes devkit', default='data/nuscenes/')
+    prep_parser.add_argument('--casr_std', help='prep casr with only standard gestures', action='store_true')
     prep_parser.add_argument('--iou_min', help='minimum iou to match ground truth', type=float, default=0.3)
     prep_parser.add_argument('--variance', help='new', action='store_true')
     prep_parser.add_argument('--activity', help='new', action='store_true')
@@ -151,11 +152,8 @@ def main():
             prep = PreprocessNuscenes(args.dir_ann, args.dir_nuscenes, args.dataset, args.iou_min)
             prep.run()
         elif 'casr' in args.dataset:
-            from .prep.casr_preprocess import create_dic
+            from .prep import create_dic
-            create_dic(std=False)
+            create_dic(dir_ann=args.dir_ann, std=args.casr_std)
-        elif 'casr_std' in args.dataset:
-            from .prep.casr_preprocess import create_dic
-            create_dic(std=True)
         else:
             from .prep.preprocess_kitti import PreprocessKitti
             prep = PreprocessKitti(args.dir_ann, mode=args.mode, iou_min=args.iou_min)