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√(noham)² 2024-07-23 16:09:32 +02:00
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commit 25207230c6
124 changed files with 7850 additions and 26104 deletions
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VoTT-v2/yolov7x-datasetv2_2024072211/hyp.yaml Normal file
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lr0: 0.01
lrf: 0.1
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 0.05
cls: 0.3
cls_pw: 1.0
obj: 0.7
obj_pw: 1.0
iou_t: 0.2
anchor_t: 4.0
fl_gamma: 0.0
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.2
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
mosaic: 1.0
mixup: 0.0
copy_paste: 0.0
paste_in: 0.0

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VoTT-v2/yolov7x-datasetv2_2024072211/opt.yaml Normal file
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dataset: datasetv2_20240722_
weights: ''
cfg: cfg/training/yolov7x_datasetv2.yaml
data: data/datasetv2/dataset.yaml
hyp: data/hyp.scratch.custom.yaml
epochs: 600
batch_size: 4
img_size:
- 1280
- 720
rect: false
resume: false
nosave: false
notest: false
noautoanchor: false
evolve: false
bucket: ''
cache_images: false
image_weights: false
device: "0\U0001F972"
multi_scale: false
single_cls: false
adam: false
sync_bn: false
local_rank: -1
workers: 1
project: runs/train
entity: null
name: yolov7x-datasetv2_20240722
exist_ok: false
quad: false
linear_lr: false
label_smoothing: 0.0
upload_dataset: false
bbox_interval: -1
save_period: -1
artifact_alias: latest
world_size: 1
global_rank: -1
save_dir: runs/train/yolov7x-datasetv2_2024072211
total_batch_size: 4

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2
test/yolov7-tracker/tracker/track_demo.py
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@ -175,7 +175,7 @@ def main(args):
exit(0)
"""3. load sequences"""
print('stride', stride)
dataset = DemoDataset(file_name=args.obj, img_size=model_img_size, model=args.detector, stride=stride, )
data_loader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=False)

3
test/yolov7-tracker/tracker/tracker_dataloader.py
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@ -103,10 +103,9 @@ class TestDataset(Dataset):
padded_img = padded_img.transpose(swap)
padded_img = np.ascontiguousarray(padded_img, dtype=np.float32)
return padded_img, r
def _preprocess_yolov7(self, img, ):
img_resized = self._letterbox(img, new_shape=self.img_size, stride=self.other_param['stride'], )[0]
img_resized = self._letterbox(img, new_shape=self.img_size, stride=32, )[0]
img_resized = img_resized[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB
img_resized = np.ascontiguousarray(img_resized)

12
test/yolov7-tracker/tracker/trackers/matching.py
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@ -69,13 +69,13 @@ def ious(atlbrs, btlbrs):
:rtype ious np.ndarray
"""
ious = np.zeros((len(atlbrs), len(btlbrs)), dtype=np.float)
ious = np.zeros((len(atlbrs), len(btlbrs)), dtype=np.float64)
if ious.size == 0:
return ious
ious = bbox_ious(
np.ascontiguousarray(atlbrs, dtype=np.float),
np.ascontiguousarray(btlbrs, dtype=np.float)
np.ascontiguousarray(atlbrs, dtype=np.float64),
np.ascontiguousarray(btlbrs, dtype=np.float64)
)
return ious
@ -129,13 +129,13 @@ def embedding_distance(tracks, detections, metric='cosine'):
:return: cost_matrix np.ndarray
"""
cost_matrix = np.zeros((len(tracks), len(detections)), dtype=np.float)
cost_matrix = np.zeros((len(tracks), len(detections)), dtype=np.float64)
if cost_matrix.size == 0:
return cost_matrix
det_features = np.asarray([track.curr_feat for track in detections], dtype=np.float)
det_features = np.asarray([track.curr_feat for track in detections], dtype=np.float64)
#for i, track in enumerate(tracks):
#cost_matrix[i, :] = np.maximum(0.0, cdist(track.smooth_feat.reshape(1,-1), det_features, metric))
track_features = np.asarray([track.smooth_feat for track in tracks], dtype=np.float)
track_features = np.asarray([track.smooth_feat for track in tracks], dtype=np.float64)
cost_matrix = np.maximum(0.0, cdist(track_features, det_features, metric)) # Nomalized features
return cost_matrix

6
test/yolov7-tracker/tracker/trackers/tracklet.py
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@ -32,7 +32,7 @@ class Tracklet(BaseTrack):
def __init__(self, tlwh, score, category, motion='byte'):
# initial position
self._tlwh = np.asarray(tlwh, dtype=np.float)
self._tlwh = np.asarray(tlwh, dtype=np.float64)
self.is_activated = False
self.score = score
@ -40,6 +40,8 @@ class Tracklet(BaseTrack):
# kalman
self.motion = motion
self.motion = 'sort'
motion = 'sort'
self.kalman_filter = MOTION_MODEL_DICT[motion]()
self.convert_func = self.__getattribute__('tlwh_to_' + STATE_CONVERT_DICT[motion])
@ -363,4 +365,4 @@ class Tracklet_w_depth(Tracklet):
cx = ret[0] + 0.5 * ret[2]
y2 = ret[1] + ret[3]
lendth = 2000 - y2
return np.asarray([cx, y2, lendth], dtype=np.float)
return np.asarray([cx, y2, lendth], dtype=np.float64)

36
yolov7-setup/track.md Normal file
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@ -0,0 +1,36 @@
Images :
```bash
python3 tracker/track_demo.py --device cpu --obj /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/tracking_images --detector yolov7 --tracker sort --detector_model_path /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/yolov7x-datasetv2_2024072211/weights/best.pt --save_dir /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/tracking --save_images
```
Video :
```bash
python3 tracker/track_demo.py --device cpu --obj /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/sources/2016-100m.mp4 --detector yolov7 --tracker sort --detector_model_path /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/yolov7x-datasetv2_2024072211/weights/best.pt --save_dir /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/tracking --save_videos
```
```bash
python3 tracker/track_demo.py --device cpu --obj /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/vids/400m_2.mp4 --detector yolov7 --tracker sort --detector_model_path /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/yolov7x-datasetv2_2024072211/weights/best.pt --save_dir /Users/noham/Documents/GitHub/Stage-2024/VoTT-v2/tracking --save_videos
```
Fixes :
self.other_param['stride'] -> 32
np.float64 in /tracker/trackers/tracklet.py
File "/Users/noham/Documents/GitHub/Stage-2024/test/yolov7-tracker/tracker/trackers/tracklet.py", line 44, in __init__
self.kalman_filter = MOTION_MODEL_DICT[motion]()
KeyError: 'default'
line 43 :
self.motion = 'sort'
motion = 'sort'
```python
TRACKER_DICT = {
'sort': SortTracker,
'bytetrack': ByteTracker,
'botsort': BotTracker,
'c_bioutrack': C_BIoUTracker,
'ocsort': OCSortTracker,
'deepsort': DeepSortTracker
}
```

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