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Functions140 in github.com/KinkangLiu/Monocular_Distance_Detect

↓ 15 callersMethod__init__
(self, c1, c2, n=1, shortcut=True, g=1, e=0.5)
models/common.py:128
↓ 15 callersMethodinfo
(self, verbose=False, img_size=640)
models/yolo.py:230
↓ 6 callersMethodsave
(self, save_dir='runs/hub/exp')
models/common.py:350
↓ 5 callersMethod__init__
(self, n, weight=False)
models/experimental.py:27
↓ 5 callersMethoddisplay
(self, pprint=False, show=False, save=False, crop=False, render=False, save_dir=Path(''))
models/common.py:316
↓ 4 callersMethod__init__
(self)
layers.py:221
↓ 4 callersFunctionmetric
(k)
utils/autoanchor.py:31
↓ 4 callersMethodtolist
(self)
models/common.py:373
↓ 3 callersFunctionprint_results
(k)
utils/autoanchor.py:93
↓ 2 callersFunctionDWConv
(c1, c2, k=1, s=1, act=True)
models/common.py:28
↓ 2 callersMethod__init__
(self, c1, k=3)
utils/activations.py:49
↓ 2 callersFunctionanchor_fitness
(k)
utils/autoanchor.py:89
↓ 2 callersFunctionattempt_load
(weights, map_location=None, inplace=True)
models/experimental.py:113
↓ 2 callersFunctionautopad
(k, p=None)
models/common.py:21
↓ 2 callersFunctioncheck_anchor_order
(m)
utils/autoanchor.py:11
↓ 2 callersFunctioncheck_file_matches_md5
(checksum, fpath)
utilsd.py:90
↓ 2 callersMethodforward_once
(self, x, profile=False)
models/yolo.py:138
↓ 1 callersMethodDetect
(self, weights='yolov5s.pt', source='data/images', # file/dir/URL/glob, 0 for webcam
estimate_distance.py:104
↓ 1 callersMethod__init__
(self, num_layers, pretrained, num_input_images=1)
networks/resnet_encoder.py:65
↓ 1 callersMethod__init__
(self, cfg='yolov5s.yaml', ch=3, nc=None, anchors=None)
models/yolo.py:79
↓ 1 callersMethod_descale_pred
(self, p, flips, scale, img_size)
models/yolo.py:161
↓ 1 callersMethod_initialize_biases
(self, cf=None)
models/yolo.py:178
↓ 1 callersMethod_make_grid
(nx=20, ny=20)
models/yolo.py:73
↓ 1 callersFunctionaddAnnoItem
(object_name, image_id, category_id, bbox)
DataPreprocessing.py:59
↓ 1 callersFunctionaddCatItem
(name)
DataPreprocessing.py:28
↓ 1 callersFunctionaddImgItem
(file_name, size)
DataPreprocessing.py:40
↓ 1 callersMethodcamera_parameters
(self, excel_path)
estimate_distance.py:40
↓ 1 callersFunctiondata_augment
(image_path, save_image_path = None)
DataPreprocessing.py:360
↓ 1 callersFunctiondel_images
该函数用于删除未标注的图片 :param xml_path: xml标注文件夹绝对路径 :param image_path: 图片文件夹绝对路径 :return: 删除的图片列表
DataPreprocessing.py:185
↓ 1 callersFunctiondisp_to_depth
Convert network's sigmoid output into depth prediction The formula for this conversion is given in the 'additional considerations' section of
layers.py:16
↓ 1 callersMethoddistance
(self, kuang, xw=5, yw=0.1)
estimate_distance.py:85
↓ 1 callersFunctiondownload_model_if_doesnt_exist
If pretrained kitti model doesn't exist, download and unzip it
utilsd.py:51
↓ 1 callersFunctionexport
(weights='./yolov5s.pt', # weights path img_size=(640, 640), # image (height, width) b
models/export.py:27
↓ 1 callersMethodforward
(self, x, augment=False, profile=False)
models/yolo.py:119
↓ 1 callersMethodforward_augment
(self, x)
models/yolo.py:125
↓ 1 callersMethodfuse
(self)
models/yolo.py:200
↓ 1 callersFunctionget_translation_matrix
Convert a translation vector into a 4x4 transformation matrix
layers.py:48
↓ 1 callersFunctionkmean_anchors
Creates kmeans-evolved anchors from training dataset Arguments: path: path to dataset *.yaml, or a loaded dataset n:
utils/autoanchor.py:61
↓ 1 callersMethodobject_point_world_position
(self, u, v, w, h, p, k)
estimate_distance.py:49
↓ 1 callersFunctionparseXmlFiles
(xml_path)
DataPreprocessing.py:91
↓ 1 callersFunctionparse_args
()
test_simple.py:26
↓ 1 callersFunctionparse_model
(d, ch)
models/yolo.py:234
↓ 1 callersFunctionresnet_multiimage_input
Constructs a ResNet model. Args: num_layers (int): Number of resnet layers. Must be 18 or 50 pretrained (bool): If True, returns a
networks/resnet_encoder.py:42
↓ 1 callersFunctionrot_from_axisangle
Convert an axisangle rotation into a 4x4 transformation matrix (adapted from https://github.com/Wallacoloo/printipi) Input 'vec' has to be Bx1
layers.py:64
↓ 1 callersFunctionsec_to_hm
Convert time in seconds to time in hours, minutes and seconds e.g. 10239 -> (2, 50, 39)
utilsd.py:31
↓ 1 callersMethodshow
(self)
models/common.py:347
↓ 1 callersFunctionsplit_data
按比例rate将数据集划分为训练集和验证集,并检查图片与标注文件的对应性 :param image_path: 已标注图片路径 :param ann_path: 标注文件路径 :param save_split_path: 划分数据集保存的路径 :param rate: 划分给训练集的比
DataPreprocessing.py:248
↓ 1 callersFunctiontest_simple
Function to predict for a single image or folder of images
test_simple.py:53
↓ 1 callersFunctionupsample
Upsample input tensor by a factor of 2
layers.py:196
↓ 1 callersFunctionvisualize
(original, augmented)
DataPreprocessing.py:385
Method__init__
(self, in_channels, out_channels)
layers.py:109
Method__init__
(self, in_channels, out_channels, use_refl=True)
layers.py:124
Method__init__
(self, batch_size, height, width)
layers.py:142
Method__init__
(self, batch_size, height, width, eps=1e-7)
layers.py:174
Method__init__
(self)
estimate_distance.py:35
Method__init__
(self, c1)
utils/activations.py:65
Method__init__
(self, c1, k=1, s=1, r=16)
utils/activations.py:82
Method__init__
(self, num_ch_enc, scales=range(4), num_output_channels=1, use_skips=True)
networks/depth_decoder.py:18
Method__init__
(self, num_input_frames)
networks/pose_cnn.py:14
Method__init__
(self, num_ch_enc, num_input_features, num_frames_to_predict_for=None, stride=1)
networks/pose_decoder.py:15
Method__init__
(self, block, layers, num_classes=1000, num_input_images=1)
networks/resnet_encoder.py:21
Method__init__
(self, nc=80, anchors=(), ch=(), inplace=True)
models/yolo.py:35
Method__init__
(self, c1, c2, k=1, s=1, p=None, g=1, act=True)
models/common.py:35
Method__init__
(self, c, num_heads)
models/common.py:50
Method__init__
(self, c1, c2, num_heads, num_layers)
models/common.py:67
Method__init__
(self, c1, c2, shortcut=True, g=1, e=0.5)
models/common.py:96
Method__init__
(self, c1, c2, n=1, shortcut=True, g=1, e=0.5)
models/common.py:109
Method__init__
(self, c1, c2, n=1, shortcut=True, g=1, e=0.5)
models/common.py:143
Method__init__
(self, c1, c2, k=(5, 9, 13))
models/common.py:151
Method__init__
(self, c1, c2, k=1, s=1, p=None, g=1, act=True)
models/common.py:165
Method__init__
(self, gain=2)
models/common.py:177
Method__init__
(self, gain=2)
models/common.py:191
Method__init__
(self, dimension=1)
models/common.py:205
Method__init__
(self)
models/common.py:220
Method__init__
(self, model)
models/common.py:234
Method__init__
(self, imgs, pred, files, times=None, names=None, shape=None)
models/common.py:300
Method__init__
(self, c1, c2, k=1, s=1, p=None, g=1)
models/common.py:387
Method__init__
(self, c1, c2, k=3, s=1, g=1, e=1.0, shortcut=False)
models/experimental.py:13
Method__init__
(self, c1, c2, k=1, s=1, g=1, act=True)
models/experimental.py:48
Method__init__
(self, c1, c2, k=3, s=1)
models/experimental.py:61
Method__init__
(self, c1, c2, k=(1, 3), s=1, equal_ch=True)
models/experimental.py:76
Method__init__
(self)
models/experimental.py:100
Method__len__
(self)
models/common.py:381
Method_print_biases
(self)
models/yolo.py:188
Methodautoshape
(self)
models/yolo.py:224
Methodautoshape
(self)
models/common.py:238
Methodbackward
(ctx, grad_output)
utils/activations.py:37
Functioncheck_anchors
(dataset, model, thr=4.0, imgsz=640)
utils/autoanchor.py:22
Functioncompute_depth_errors
Computation of error metrics between predicted and ground truth depths
layers.py:251
Methodcrop
(self, save_dir='runs/hub/exp')
models/common.py:354
Methodforward
(self, x)
layers.py:115
Methodforward
(self, x)
layers.py:133
Methodforward
(self, depth, inv_K)
layers.py:163
Methodforward
(self, points, K, T)
layers.py:182
Methodforward
(self, x, y)
layers.py:234
Methodforward
(x)
utils/activations.py:11
Methodforward
(x)
utils/activations.py:17
Methodforward
(x)
utils/activations.py:25
Methodforward
(ctx, x)
utils/activations.py:32
Methodforward
(self, x)
utils/activations.py:43
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