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  1. .gitignore +1 -0
  2. Code/Inference.py +275 -0
  3. Code/__pycache__/Inference.cpython-311.pyc +0 -0
  4. Repositories/DeepLabCut-live/.gitignore +139 -0
  5. Repositories/DeepLabCut-live/CITATION.cff +55 -0
  6. Repositories/DeepLabCut-live/LICENSE +666 -0
  7. Repositories/DeepLabCut-live/MANIFEST.in +1 -0
  8. Repositories/DeepLabCut-live/README.md +153 -0
  9. Repositories/DeepLabCut-live/benchmarking/run_dlclive_benchmark.py +43 -0
  10. Repositories/DeepLabCut-live/dlclive/__init__.py +11 -0
  11. Repositories/DeepLabCut-live/dlclive/benchmark.py +726 -0
  12. Repositories/DeepLabCut-live/dlclive/check_install/check_install.py +88 -0
  13. Repositories/DeepLabCut-live/dlclive/display.py +117 -0
  14. Repositories/DeepLabCut-live/dlclive/dlclive.py +480 -0
  15. Repositories/DeepLabCut-live/dlclive/exceptions.py +18 -0
  16. Repositories/DeepLabCut-live/dlclive/graph.py +138 -0
  17. Repositories/DeepLabCut-live/dlclive/pose.py +120 -0
  18. Repositories/DeepLabCut-live/dlclive/processor/README.md +21 -0
  19. Repositories/DeepLabCut-live/dlclive/processor/__init__.py +9 -0
  20. Repositories/DeepLabCut-live/dlclive/processor/kalmanfilter.py +144 -0
  21. Repositories/DeepLabCut-live/dlclive/processor/processor.py +23 -0
  22. Repositories/DeepLabCut-live/dlclive/utils.py +218 -0
  23. Repositories/DeepLabCut-live/dlclive/version.py +11 -0
  24. Repositories/DeepLabCut-live/docs/install_desktop.md +29 -0
  25. Repositories/DeepLabCut-live/docs/install_jetson.md +81 -0
  26. Repositories/DeepLabCut-live/example_processors/DogJumpLED/__init__.py +9 -0
  27. Repositories/DeepLabCut-live/example_processors/DogJumpLED/izzy_jump.py +143 -0
  28. Repositories/DeepLabCut-live/example_processors/DogJumpLED/izzy_jump_offline.py +123 -0
  29. Repositories/DeepLabCut-live/example_processors/DogJumpLED/teensy_leds/teensy_leds.ino +49 -0
  30. Repositories/DeepLabCut-live/example_processors/MouseLickLED/__init__.py +8 -0
  31. Repositories/DeepLabCut-live/example_processors/MouseLickLED/lick_led.py +85 -0
  32. Repositories/DeepLabCut-live/example_processors/MouseLickLED/teensy_leds/teensy_leds.ino +49 -0
  33. Repositories/DeepLabCut-live/example_processors/TeensyLaser/__init__.py +8 -0
  34. Repositories/DeepLabCut-live/example_processors/TeensyLaser/teensy_laser.py +86 -0
  35. Repositories/DeepLabCut-live/example_processors/TeensyLaser/teensy_laser/teensy_laser.ino +77 -0
  36. Repositories/DeepLabCut-live/poetry.lock +0 -0
  37. Repositories/DeepLabCut-live/pyproject.toml +46 -0
  38. Repositories/DeepLabCut-live/reinstall.sh +4 -0
  39. app.py +46 -0
  40. requirements.txt +8 -0
.gitignore ADDED
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1
+ Weights/
Code/Inference.py ADDED
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1
+ """
2
+ inference on single image for MaskRCNN (FROM DETECTRON) + DLC
3
+
4
+ two step, pretrained MaskRCNN, then DLC
5
+
6
+ """
7
+ import cv2
8
+ import torch
9
+
10
+ import sys
11
+ sys.path.append("Repositories/DeepLabCut-live")
12
+
13
+ import deeplabcut as dlc
14
+ from dlclive import DLCLive, Processor
15
+
16
+ import matplotlib.pyplot as plt
17
+ import numpy as np
18
+ from tqdm import tqdm
19
+ import os
20
+ import shutil
21
+
22
+ import torchvision
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+ from torchvision.transforms import transforms as transforms
24
+
25
+ import pickle
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+
27
+ import detectron2
28
+
29
+ # import some common detectron2 utilities
30
+ from detectron2 import model_zoo
31
+ from detectron2.engine import DefaultPredictor
32
+ from detectron2.config import get_cfg
33
+ from detectron2.utils.visualizer import Visualizer
34
+ from detectron2.data import MetadataCatalog, DatasetCatalog
35
+
36
+ import cv2
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+
38
+
39
+
40
+ COCO_INSTANCE_CATEGORY_NAMES = [
41
+ '__background__', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus',
42
+ 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'N/A', 'stop sign',
43
+ 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
44
+ 'elephant', 'bear', 'zebra', 'giraffe', 'N/A', 'backpack', 'umbrella', 'N/A', 'N/A',
45
+ 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball',
46
+ 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket',
47
+ 'bottle', 'N/A', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl',
48
+ 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza',
49
+ 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'N/A', 'dining table',
50
+ 'N/A', 'N/A', 'toilet', 'N/A', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
51
+ 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'N/A', 'book',
52
+ 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'
53
+ ]
54
+
55
+
56
+ def Process_Crop(Crop, CropSize):
57
+ """Crop image and pad, if too big, will scale down """
58
+ # import ipdb;ipdb.set_trace()
59
+ if Crop.shape[0] > CropSize[0] or Crop.shape[1] > CropSize[1]: #Crop is bigger, scale down
60
+ ScaleProportion = min(CropSize[0]/Crop.shape[0],CropSize[1]/Crop.shape[1])
61
+
62
+ width_scaled = int(Crop.shape[1] * ScaleProportion)
63
+ height_scaled = int(Crop.shape[0] * ScaleProportion)
64
+ Crop = cv2.resize(Crop, (width_scaled,height_scaled), interpolation=cv2.INTER_LINEAR) # resize image
65
+
66
+ # Points2D = {k:[v[0]*ScaleProportion,v[1]*ScaleProportion] for k,v in Points2D.items()}
67
+ else:
68
+ ScaleProportion = 1
69
+
70
+ if Crop.shape[0] %2 ==0:
71
+ #Shape is even number
72
+ YPadTop = int((CropSize[1] - Crop.shape[0])/2)
73
+ YPadBot = int((CropSize[1] - Crop.shape[0])/2)
74
+ else:
75
+ YPadTop = int( ((CropSize[1] - Crop.shape[0])/2)-0.5)
76
+ YPadBot = int(((CropSize[1] - Crop.shape[0])/2)+0.5)
77
+ ##Padding:
78
+ if Crop.shape[1] %2 ==0:
79
+ #Shape is even number
80
+ XPadLeft = int((CropSize[0] - Crop.shape[1])/2)
81
+ XPadRight= int((CropSize[0] - Crop.shape[1])/2)
82
+ else:
83
+ XPadLeft = int(((CropSize[0] - Crop.shape[1])/2)-0.5)
84
+ XPadRight= int(((CropSize[0] - Crop.shape[1])/2)+0.5)
85
+
86
+
87
+
88
+ OutImage = cv2.copyMakeBorder(Crop, YPadTop,YPadBot,XPadLeft,XPadRight,cv2.BORDER_CONSTANT,value=[0,0,0])
89
+
90
+ return OutImage,ScaleProportion, YPadTop,XPadLeft
91
+
92
+
93
+
94
+ def DLCInference(Crop,dlc_liveObj,CropSize):
95
+ """Inference for DLC"""
96
+
97
+ ###Scale crop if image bigger than cropsize
98
+ # import ipdb;ipdb.set_trace()
99
+ if Crop.shape[0] > CropSize[0] or Crop.shape[1] > CropSize[1]: #Image bigger than crop size, scale down
100
+ ScaleRatio = min([CropSize[0]/Crop.shape[0], CropSize[1]/Crop.shape[1]])
101
+ ScaleWidth = round(Crop.shape[1] * ScaleRatio)
102
+ ScaleHeight = round(Crop.shape[0]*ScaleRatio)
103
+ resizedCrop = cv2.resize(Crop, (ScaleWidth,ScaleHeight), interpolation=cv2.INTER_LINEAR) # resize image
104
+ ScaleUpRatio = 1/ScaleRatio #ratio to scale keypoints back up to original
105
+ # import ipdb;ipdb.set_trace()
106
+ else:
107
+ resizedCrop = Crop
108
+ ScaleUpRatio = 1
109
+ # cv2.imwrite(filename="tempresize.jpg", img=resizedCrop)
110
+ # cv2.imwrite(filename="temp.jpg", img=Crop)
111
+ if dlc_liveObj.sess == None: #if first time, init
112
+ DLCPredict2D = dlc_liveObj.init_inference(resizedCrop)
113
+
114
+ DLCPredict2D= dlc_liveObj.get_pose(resizedCrop)
115
+ DLCPredict2D[:,0] = DLCPredict2D[:,0]*ScaleUpRatio
116
+ DLCPredict2D[:,1] = DLCPredict2D[:,1]*ScaleUpRatio
117
+
118
+ return DLCPredict2D
119
+
120
+
121
+ def VisualizeAll(frame, box, DLCPredict2D,MeanConfidence,ScaleBBox, imsize):
122
+ """Visualize all stuff"""
123
+ # colourList = [(255,255,0),(255,0 ,255),(128,0,128),(203,192,255),(0, 255, 255),(255, 0 , 0 ),(63,133,205),(0,255,0),(0,0,255)]
124
+ colourList = [(0,255,255),(255,0 ,255),(128,0,128),(255,192,203),(255, 255, 0),(0, 0 , 255 ),(205,133,63),(0,255,0),(255,0,0)]
125
+
126
+ ##Order: Lshoulder, Rshoulder, topKeel,botKeel,Tail,Beak,Nose,Leye,Reye
127
+ ##Points:
128
+ PlotPoints = []
129
+ for x,point in enumerate(DLCPredict2D):
130
+ roundPoint = [round(point[0]+box[0]),round(point[1]+box[1])]
131
+ cv2.circle(frame,roundPoint,1,colourList[x], 5)
132
+ PlotPoints.append(roundPoint)
133
+
134
+
135
+ ##change box to XYWH to scale down
136
+ # bbox = [box[0],box[1],box[2]-box[0],box[3]-box[1]]
137
+ # ScaleWidth = (bbox[2]/ScaleBBox)/2
138
+ # ScaleHeight = (bbox[3]/ScaleBBox)/2
139
+ # ###based on ScaleBBox, scale back down bounding box for plotting
140
+ # x1 = round(bbox[0]+ScaleWidth) if round(bbox[0]+ScaleWidth)>0 else 0
141
+ # y1 = round(bbox[1]+ScaleHeight)if round(bbox[1]+ScaleHeight)>0 else 0
142
+ # x2 = round(bbox[0]+bbox[2]-ScaleWidth) if round(bbox[0]+bbox[2]-ScaleWidth) < imsize[0] else imsize[0]
143
+ # y2 = round(bbox[1]+bbox[3]-ScaleHeight)if round(bbox[1]+bbox[3]-ScaleHeight) < imsize[1] else imsize[1]
144
+ # box = [x1,y1,x2,y2]
145
+ cv2.rectangle(frame,(round(box[0]),round(box[1])),(round(box[2]),round(box[3])),[0,0,255],3)
146
+
147
+ #plot mean confidence
148
+ # import ipdb;ipdb.set_trace()
149
+ # font = cv2.FONT_HERSHEY_SIMPLEX
150
+ # cv2.putText(frame,str(round(MeanConfidence,3)),(round(box[0]),round(box[1])),font,2,[255,0,0],2)
151
+
152
+ return frame, PlotPoints
153
+
154
+
155
+ def Inference(frame,predictor,dlc_liveObj,ScaleBBox=1,Dilate=5,DLCThreshold=0.3):
156
+ """Loop through video for SAM, save framewise info"""
157
+
158
+ InferFrame = frame.copy()
159
+ outputs = predictor(InferFrame)["instances"].to("cpu")
160
+ CropSize = (320,320)
161
+
162
+ # import ipdb;ipdb.set_trace()
163
+ imsize = [frame.shape[1],frame.shape[0]]
164
+
165
+ BirdIndex = np.where(outputs.pred_classes.numpy() == 14)[0] #14 is ID for bird
166
+ BirdBBox = outputs.pred_boxes[BirdIndex].tensor.numpy()
167
+ # import ipdb;ipdb.set_trace()
168
+ BirdMasks = (outputs.pred_masks>0.95).numpy()[BirdIndex]
169
+
170
+ for x in range(BirdBBox.shape[0]):
171
+ # import ipdb;ipdb.set_trace()
172
+
173
+ bbox = list(BirdBBox[x])
174
+ Mask = BirdMasks[x]>0
175
+ Mask = np.array(Mask,dtype=np.uint8)
176
+ # show_anns(frame, Mask)
177
+
178
+ if Dilate > 0:
179
+ DilateKernel = np.ones((Dilate,Dilate),np.uint8)
180
+ Mask = cv2.dilate(Mask,DilateKernel,iterations = 3)
181
+
182
+ # import ipdb;ipdb.set_trace()
183
+ Mask = np.array(Mask,dtype=np.uint8)
184
+ Mask = Mask.reshape(imsize[1],imsize[0],1)
185
+ Crop = cv2.bitwise_and(InferFrame, InferFrame, mask=Mask)
186
+
187
+ # cv2.imwrite(filename="temp.jpg", img = Crop)
188
+
189
+ ##change box to XYWH to scale up
190
+ bbox = [bbox[0],bbox[1],bbox[2]-bbox[0],bbox[3]-bbox[1]]
191
+ ScaleWidth = ((ScaleBBox * bbox[2])/2)-(bbox[2]/2)
192
+ ScaleHeight = ((ScaleBBox * bbox[3])/2)-(bbox[3]/2)
193
+ # import ipdb;ipdb.set_trace()
194
+ # BirdCrop = frame[round(bbox[1]):round(bbox[3]),round(bbox[0]):round(bbox[2])] #bbox is XYWH
195
+
196
+ x1 = round(bbox[0]-ScaleWidth) if round(bbox[0]-ScaleWidth)>0 else 0
197
+ y1 = round(bbox[1]-ScaleHeight)if round(bbox[1]-ScaleHeight)>0 else 0
198
+ x2 = round(bbox[0]+bbox[2]+ScaleWidth) if round(bbox[0]+bbox[2]+ScaleWidth) < imsize[0] else imsize[0]
199
+ y2 = round(bbox[1]+bbox[3]+ScaleHeight)if round(bbox[1]+bbox[3]+ScaleHeight) < imsize[1] else imsize[1]
200
+ bbox = [x1,y1,x2,y2]
201
+ BirdCrop = Crop[y1:y2,x1:x2] #bbox is XYWH
202
+
203
+ DLCPredict2D= DLCInference(BirdCrop,dlc_liveObj,CropSize)
204
+ MeanConfidence = DLCPredict2D[:,2].mean()
205
+
206
+ if MeanConfidence > DLCThreshold: #if mean keypoint confidence is higher than this threshold, consider bird
207
+ bbox.append(MeanConfidence)
208
+ frame, PlotPoints = VisualizeAll(frame, bbox, DLCPredict2D,MeanConfidence,ScaleBBox,imsize)
209
+
210
+ if BirdBBox.shape[0] == 0:
211
+ DLCPredict2D= DLCInference(InferFrame,dlc_liveObj,CropSize)
212
+ MeanConfidence = DLCPredict2D[:,2].mean()
213
+ bbox = [0,0,0,0]
214
+ if MeanConfidence > DLCThreshold: #if mean keypoint confidence is higher than this threshold, consider bird
215
+ frame, PlotPoints = VisualizeAll(frame, bbox, DLCPredict2D,MeanConfidence,ScaleBBox,imsize)
216
+
217
+ return frame
218
+
219
+
220
+
221
+
222
+ if __name__ == "__main__":
223
+ # VidPath = "/media/alexchan/Extreme SSD/WorkDir/Pigeon3DTrack/ManualClickTrials/Videos/Cam1_C0008.MP4_Trimmed.mp4"
224
+ VidPath = "/media/alexchan/Extreme SSD/SampleDatasets/PigeonsEverywhere/2022-12-01_Pilot_bottom_control.mp4"
225
+
226
+ OutDir = "/media/alexchan/Extreme SSD/WorkDir/Pigeon3DTrack/OutdoorTracking/Final2D"
227
+
228
+ ExportModelPath = "/media/alexchan/Extreme SSD/WorkDir/Pigeon3DTrack/Weights/DLC_Weights/N6000_DLC_Mask/exported-models/DLC_DLC_Segmented_resnet_50_iteration-0_shuffle-1"
229
+ # ExportModelPath = "/media/alexchan/Extreme SSD/WorkDir/Pigeon3DTrack/Weights/DLC_Weights/DLC_PigeonSuperModel_imgaug_efficientnet-b0_iteration-0_shuffle-2"
230
+
231
+ if not os.path.isdir(ExportModelPath):
232
+ #need to export model first
233
+ # DLC_Config = "/media/alexchan/Extreme SSD/SampleDatasets/ImageTrainingData/N5000/DLC_Seg_Aug/config.yaml"
234
+
235
+ dlc.export_model(DLC_Config)
236
+ else:
237
+ print("model already exported!")
238
+
239
+ CropSize = (320,320)
240
+ # WeightPath = "/home/alexchan/Documents/Pigeon3DTrack/Data/YOLO_Weights/yolov8m.pt"
241
+ # VidPath= "/media/alexchan/Extreme SSD/PigeonOutdoors/28032023/Cam1_C0004.MP4"
242
+ # import ipdb;ipdb.set_trace()
243
+ # YOLOModel = YOLO(YOLOPath)
244
+ device = "cuda"
245
+ # device = "cpu"
246
+
247
+ ###Detectron:
248
+ cfg = get_cfg()
249
+ # add project-specific config (e.g., TensorMask) here if you're not running a model in detectron2's core library
250
+ cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml"))
251
+ cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.7 # set threshold for this model
252
+ # Find a model from detectron2's model zoo. You can use the https://dl.fbaipublicfiles... url as well
253
+ cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml")
254
+ predictor = DefaultPredictor(cfg)
255
+
256
+
257
+ ##DLC:
258
+ dlc_proc = Processor()
259
+ dlc_liveObj = DLCLive(ExportModelPath, processor=dlc_proc)
260
+
261
+ RunInference(predictor,dlc_liveObj, device,OutDir,
262
+ VidPath,CropSize,startFrame=0,
263
+ TotalFrames =900, ScaleBBox=1.3,
264
+ DLCThreshold = 0, Dilate=5)
265
+
266
+
267
+
268
+ ###DLC tests
269
+ # DLC_Config = "/media/alexchan/Extreme SSD/SampleDatasets/ImageTrainingData/N5000/DLC/config.yaml"
270
+ # Video = "/media/alexchan/Extreme SSD/SampleDatasets/ImageTrainingData/N5000/DLC/videos/Video1.mp4"
271
+ # dlc.analyze_videos(DLC_Config,[Video])
272
+ # dlc.export_model(DLC_Config)
273
+
274
+ # import pandas as pd
275
+ # pd.read_hdf("/media/alexchan/Extreme SSD/SampleDatasets/ImageTrainingData/N5000/DLC/videos/Video1DLC_resnet50_DLC20230401-173058shuffle1_3000.h5")
Code/__pycache__/Inference.cpython-311.pyc ADDED
Binary file (12.1 kB). View file
Repositories/DeepLabCut-live/.gitignore ADDED
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1
+ # DeepLabCut-live
2
+
3
+ # Data related to benchmark!
4
+ benchmarking/Data*
5
+ benchmarking/results*
6
+
7
+ *test*
8
+ **DS_Store*
9
+ *vscode*
10
+
11
+ # Byte-compiled / optimized / DLL files
12
+ __pycache__/
13
+ *.py[cod]
14
+ *$py.class
15
+
16
+ # C extensions
17
+ *.so
18
+
19
+ # Distribution / packaging
20
+ .Python
21
+ build/
22
+ develop-eggs/
23
+ dist/
24
+ downloads/
25
+ eggs/
26
+ .eggs/
27
+ lib/
28
+ lib64/
29
+ parts/
30
+ sdist/
31
+ var/
32
+ wheels/
33
+ pip-wheel-metadata/
34
+ share/python-wheels/
35
+ *.egg-info/
36
+ .installed.cfg
37
+ *.egg
38
+ MANIFEST
39
+
40
+ # PyInstaller
41
+ # Usually these files are written by a python script from a template
42
+ # before PyInstaller builds the exe, so as to inject date/other infos into it.
43
+ *.manifest
44
+ *.spec
45
+
46
+ # Installer logs
47
+ pip-log.txt
48
+ pip-delete-this-directory.txt
49
+
50
+ # Unit test / coverage reports
51
+ htmlcov/
52
+ .tox/
53
+ .nox/
54
+ .coverage
55
+ .coverage.*
56
+ .cache
57
+ nosetests.xml
58
+ coverage.xml
59
+ *.cover
60
+ *.py,cover
61
+ .hypothesis/
62
+ .pytest_cache/
63
+
64
+ # Translations
65
+ *.mo
66
+ *.pot
67
+
68
+ # Django stuff:
69
+ *.log
70
+ local_settings.py
71
+ db.sqlite3
72
+ db.sqlite3-journal
73
+
74
+ # Flask stuff:
75
+ instance/
76
+ .webassets-cache
77
+
78
+ # Scrapy stuff:
79
+ .scrapy
80
+
81
+ # Sphinx documentation
82
+ docs/_build/
83
+
84
+ # PyBuilder
85
+ target/
86
+
87
+ # Jupyter Notebook
88
+ .ipynb_checkpoints
89
+
90
+ # IPython
91
+ profile_default/
92
+ ipython_config.py
93
+
94
+ # pyenv
95
+ .python-version
96
+
97
+ # pipenv
98
+ # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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+ # However, in case of collaboration, if having platform-specific dependencies or dependencies
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+ # having no cross-platform support, pipenv may install dependencies that don't work, or not
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+ # install all needed dependencies.
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+ #Pipfile.lock
103
+
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+ # PEP 582; used by e.g. github.com/David-OConnor/pyflow
105
+ __pypackages__/
106
+
107
+ # Celery stuff
108
+ celerybeat-schedule
109
+ celerybeat.pid
110
+
111
+ # SageMath parsed files
112
+ *.sage.py
113
+
114
+ # Environments
115
+ .env
116
+ .venv
117
+ env/
118
+ venv/
119
+ ENV/
120
+ env.bak/
121
+ venv.bak/
122
+
123
+ # Spyder project settings
124
+ .spyderproject
125
+ .spyproject
126
+
127
+ # Rope project settings
128
+ .ropeproject
129
+
130
+ # mkdocs documentation
131
+ /site
132
+
133
+ # mypy
134
+ .mypy_cache/
135
+ .dmypy.json
136
+ dmypy.json
137
+
138
+ # Pyre type checker
139
+ .pyre/
Repositories/DeepLabCut-live/CITATION.cff ADDED
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1
+ # This CITATION.cff file was generated with cffinit.
2
+ # Visit https://bit.ly/cffinit to generate yours today!
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+
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+ cff-version: 1.2.0
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+ title: >-
6
+ Real-time, low-latency closed-loop feedback using
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+ markerless posture tracking
8
+ message: >-
9
+ If you utilize our tool, please [cite Kane et al,
10
+ eLife
11
+ 2020](https://elifesciences.org/articles/61909).
12
+ The preprint is available here:
13
+ https://www.biorxiv.org/content/10.1101/2020.08.04.236422v2
14
+ type: article
15
+ authors:
16
+ - given-names: Gary
17
+ name-particle: A
18
+ family-names: Kane
19
+ affiliation: >-
20
+ The Rowland Institute at Harvard, Harvard
21
+ University, Cambridge, United States
22
+ - given-names: Gonçalo
23
+ family-names: Lopes
24
+ affiliation: 'NeuroGEARS Ltd, London, United Kingdom'
25
+ - given-names: Jonny
26
+ name-particle: L
27
+ family-names: Saunders
28
+ affiliation: >-
29
+ Institute of Neuroscience, Department of
30
+ Psychology, University of Oregon, Eugene,
31
+ United States
32
+ - given-names: Alexander
33
+ family-names: Mathis
34
+ affiliation: >-
35
+ The Rowland Institute at Harvard, Harvard
36
+ University, Cambridge, United States; Center
37
+ for Neuroprosthetics, Center for Intelligent
38
+ Systems, & Brain Mind Institute, School of Life
39
+ Sciences, Swiss Federal Institute of Technology
40
+ (EPFL), Lausanne, Switzerland
41
+ - given-names: Mackenzie
42
+ name-particle: W
43
+ family-names: Mathis
44
+ affiliation: >-
45
+ The Rowland Institute at Harvard, Harvard
46
+ University, Cambridge, United States; Center
47
+ for Neuroprosthetics, Center for Intelligent
48
+ Systems, & Brain Mind Institute, School of Life
49
+ Sciences, Swiss Federal Institute of Technology
50
+ (EPFL), Lausanne, Switzerland
51
+ email: mackenzie.mathis@epfl.ch
52
+ date-released: 2020-08-05
53
+ doi: "10.7554/eLife.61909"
54
+ license: "AGPL-3.0-or-later"
55
+ version: "1.0.3"
Repositories/DeepLabCut-live/LICENSE ADDED
@@ -0,0 +1,666 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ Copyright 2020-2022 by Mackenzie Mathis, Gary Kane, Alexander Mathis and contributors. All rights reserved.
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Repositories/DeepLabCut-live/MANIFEST.in ADDED
@@ -0,0 +1 @@
 
1
+ include dlclive/check_install/*
Repositories/DeepLabCut-live/README.md ADDED
@@ -0,0 +1,153 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # DeepLabCut-live! SDK<img src="https://images.squarespace-cdn.com/content/v1/57f6d51c9f74566f55ecf271/1606082050387-M8M1CFI5DFUZCBAAUI0W/ke17ZwdGBToddI8pDm48kLuMKy7Ws6mFofiFehYynfdZw-zPPgdn4jUwVcJE1ZvWQUxwkmyExglNqGp0IvTJZUJFbgE-7XRK3dMEBRBhUpzp2tFVMcEgqZM8QO7VXXQogrsLnYKC4n4YnYuHC1HMRWygQlqMNAoTF9HaycikLeg/DLClive.png?format=750w" width="350" title="DLC-live" alt="DLC LIVE!" align="right" vspace = "50">
2
+
3
+ <a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
4
+ ![PyPI - Python Version](https://img.shields.io/pypi/v/deeplabcut-live)
5
+ [![Downloads](https://pepy.tech/badge/deeplabcut-live)](https://pepy.tech/project/deeplabcut-live)
6
+ [![Downloads](https://pepy.tech/badge/deeplabcut-live/month)](https://pepy.tech/project/deeplabcut-live)
7
+ ![Python package](https://github.com/DeepLabCut/DeepLabCut-live/workflows/Python%20package/badge.svg)
8
+ [![GitHub stars](https://img.shields.io/github/stars/DeepLabCut/DeepLabCut-live.svg?style=social&label=Star)](https://github.com/DeepLabCut/DeepLabCut-live)
9
+ [![GitHub forks](https://img.shields.io/github/forks/DeepLabCut/DeepLabCut-live.svg?style=social&label=Fork)](https://github.com/DeepLabCut/DeepLabCut-live)
10
+ [![Image.sc forum](https://img.shields.io/badge/dynamic/json.svg?label=forum&amp;url=https%3A%2F%2Fforum.image.sc%2Ftags%2Fdeeplabcut.json&amp;query=%24.topic_list.tags.0.topic_count&amp;colorB=brightgreen&amp;&amp;suffix=%20topics&amp;logo=data:image/png;base64,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)](https://forum.image.sc/tags/deeplabcut)
11
+ [![Gitter](https://badges.gitter.im/DeepLabCut/community.svg)](https://gitter.im/DeepLabCut/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
12
+ [![Twitter Follow](https://img.shields.io/twitter/follow/DeepLabCut.svg?label=DeepLabCut&style=social)](https://twitter.com/DeepLabCut)
13
+
14
+ This package contains a [DeepLabCut](http://www.mousemotorlab.org/deeplabcut) inference pipeline for real-time applications that has minimal (software) dependencies. Thus, it is as easy to install as possible (in particular, on atypical systems like [NVIDIA Jetson boards](https://developer.nvidia.com/buy-jetson)).
15
+
16
+ **Performance:** If you would like to see estimates on how your model should perform given different video sizes, neural network type, and hardware, please see: https://deeplabcut.github.io/DLC-inferencespeed-benchmark/
17
+
18
+ If you have different hardware, please consider submitting your results too! https://github.com/DeepLabCut/DLC-inferencespeed-benchmark
19
+
20
+ **What this SDK provides:** This package provides a `DLCLive` class which enables pose estimation online to provide feedback. This object loads and prepares a DeepLabCut network for inference, and will return the predicted pose for single images.
21
+
22
+ To perform processing on poses (such as predicting the future pose of an animal given it's current pose, or to trigger external hardware like send TTL pulses to a laser for optogenetic stimulation), this object takes in a `Processor` object. Processor objects must contain two methods: process and save.
23
+
24
+ - The `process` method takes in a pose, performs some processing, and returns processed pose.
25
+ - The `save` method saves any valuable data created by or used by the processor
26
+
27
+ For more details and examples, see documentation [here](dlclive/processor/README.md).
28
+
29
+ ###### 🔥🔥🔥🔥🔥 Note :: alone, this object does not record video or capture images from a camera. This must be done separately, i.e. see our [DeepLabCut-live GUI](https://github.com/gkane26/DeepLabCut-live-GUI).🔥🔥🔥
30
+
31
+ ### News!
32
+ - March 2022: DeepLabCut-Live! 1.0.2 supports poetry installation `poetry install deeplabcut-live`, thanks to PR #60.
33
+ - March 2021: DeepLabCut-Live! [**version 1.0** is released](https://pypi.org/project/deeplabcut-live/), with support for tensorflow 1 and tensorflow 2!
34
+ - Feb 2021: DeepLabCut-Live! was featured in **Nature Methods**: ["Real-time behavioral analysis"](https://www.nature.com/articles/s41592-021-01072-z)
35
+ - Jan 2021: full **eLife** paper is published: ["Real-time, low-latency closed-loop feedback using markerless posture tracking"](https://elifesciences.org/articles/61909)
36
+ - Dec 2020: we talked to **RTS Suisse Radio** about DLC-Live!: ["Capture animal movements in real time"](https://www.rts.ch/play/radio/cqfd/audio/capturer-les-mouvements-des-animaux-en-temps-reel?id=11782529)
37
+
38
+
39
+ ### Installation:
40
+
41
+ Please see our instruction manual to install on a [Windows or Linux machine](docs/install_desktop.md) or on a [NVIDIA Jetson Development Board](docs/install_jetson.md). Note, this code works with tensorflow (TF) 1 or TF 2 models, but TF requires that whatever version you exported your model with, you must import with the same version (i.e., export with TF1.13, then use TF1.13 with DlC-Live; export with TF2.3, then use TF2.3 with DLC-live).
42
+
43
+ - available on pypi as: `pip install deeplabcut-live`
44
+
45
+ Note, you can then test your installation by running:
46
+
47
+ `dlc-live-test`
48
+
49
+ If installed properly, this script will i) create a temporary folder ii) download the full_dog model from the [DeepLabCut Model Zoo](http://www.mousemotorlab.org/dlc-modelzoo), iii) download a short video clip of a dog, and iv) run inference while displaying keypoints. v) remove the temporary folder.
50
+
51
+ <img src="https://images.squarespace-cdn.com/content/v1/57f6d51c9f74566f55ecf271/1606081086014-TG9GWH63ZGGOO7K779G3/ke17ZwdGBToddI8pDm48kHiSoSToKfKUI9t99vKErWoUqsxRUqqbr1mOJYKfIPR7LoDQ9mXPOjoJoqy81S2I8N_N4V1vUb5AoIIIbLZhVYxCRW4BPu10St3TBAUQYVKcOoIGycwr1shdgJWzLuxyzjLbSRGBFFxjYMBr42yCvRK5HHsLZWtMlAHzDU294nCd/dlclivetest.png?format=1000w" width="650" title="DLC-live-test" alt="DLC LIVE TEST" align="center" vspace = "50">
52
+
53
+ ### Quick Start: instructions for use:
54
+
55
+ 1. Initialize `Processor` (if desired)
56
+ 2. Initialize the `DLCLive` object
57
+ 3. Perform pose estimation!
58
+
59
+ ```python
60
+ from dlclive import DLCLive, Processor
61
+ dlc_proc = Processor()
62
+ dlc_live = DLCLive(<path to exported model directory>, processor=dlc_proc)
63
+ dlc_live.init_inference(<your image>)
64
+ dlc_live.get_pose(<your image>)
65
+ ```
66
+
67
+ `DLCLive` **parameters:**
68
+
69
+ - `path` = string; full path to the exported DLC model directory
70
+ - `model_type` = string; the type of model to use for inference. Types include:
71
+ - `base` = the base DeepLabCut model
72
+ - `tensorrt` = apply [tensor-rt](https://developer.nvidia.com/tensorrt) optimizations to model
73
+ - `tflite` = use [tensorflow lite](https://www.tensorflow.org/lite) inference (in progress...)
74
+ - `cropping` = list of int, optional; cropping parameters in pixel number: [x1, x2, y1, y2]
75
+ - `dynamic` = tuple, optional; defines parameters for dynamic cropping of images
76
+ - `index 0` = use dynamic cropping, bool
77
+ - `index 1` = detection threshold, float
78
+ - `index 2` = margin (in pixels) around identified points, int
79
+ - `resize` = float, optional; factor by which to resize image (resize=0.5 downsizes both width and height of image by half). Can be used to downsize large images for faster inference
80
+ - `processor` = dlc pose processor object, optional
81
+ - `display` = bool, optional; display processed image with DeepLabCut points? Can be used to troubleshoot cropping and resizing parameters, but is very slow
82
+
83
+ `DLCLive` **inputs:**
84
+
85
+ - `<path to exported model directory>` = path to the folder that has the `.pb` files that you acquire after running `deeplabcut.export_model`
86
+ - `<your image>` = is a numpy array of each frame
87
+
88
+
89
+ ### Benchmarking/Analyzing your exported DeepLabCut models
90
+
91
+ DeepLabCut-live offers some analysis tools that allow users to peform the following operations on videos, from python or from the command line:
92
+
93
+ 1. Test inference speed across a range of image sizes, downsizing images by specifying the `resize` or `pixels` parameter. Using the `pixels` parameter will resize images to the desired number of `pixels`, without changing the aspect ratio. Results will be saved (along with system info) to a pickle file if you specify an output directory.
94
+ ##### python
95
+ ```python
96
+ dlclive.benchmark_videos('/path/to/exported/model', ['/path/to/video1', '/path/to/video2'], output='/path/to/output', resize=[1.0, 0.75, '0.5'])
97
+ ```
98
+ ##### command line
99
+ ```
100
+ dlc-live-benchmark /path/to/exported/model /path/to/video1 /path/to/video2 -o /path/to/output -r 1.0 0.75 0.5
101
+ ```
102
+
103
+ 2. Display keypoints to visually inspect the accuracy of exported models on different image sizes (note, this is slow and only for testing purposes):
104
+
105
+ ##### python
106
+ ```python
107
+ dlclive.benchmark_videos('/path/to/exported/model', '/path/to/video', resize=0.5, display=True, pcutoff=0.5, display_radius=4, cmap='bmy')
108
+ ```
109
+ ##### command line
110
+ ```
111
+ dlc-live-benchmark /path/to/exported/model /path/to/video -r 0.5 --display --pcutoff 0.5 --display-radius 4 --cmap bmy
112
+ ```
113
+
114
+ 3. Analyze and create a labeled video using the exported model and desired resize parameters. This option functions similar to `deeplabcut.benchmark_videos` and `deeplabcut.create_labeled_video` (note, this is slow and only for testing purposes).
115
+
116
+ ##### python
117
+ ```python
118
+ dlclive.benchmark_videos('/path/to/exported/model', '/path/to/video', resize=[1.0, 0.75, 0.5], pcutoff=0.5, display_radius=4, cmap='bmy', save_poses=True, save_video=True)
119
+ ```
120
+ ##### command line
121
+ ```
122
+ dlc-live-benchmark /path/to/exported/model /path/to/video -r 0.5 --pcutoff 0.5 --display-radius 4 --cmap bmy --save-poses --save-video
123
+ ```
124
+
125
+ ## License:
126
+
127
+ This project is licensed under the GNU AGPLv3. Note that the software is provided "as is", without warranty of any kind, express or implied. If you use the code or data, we ask that you please cite us! This software is available for licensing via the EPFL Technology Transfer Office (https://tto.epfl.ch/, info.tto@epfl.ch).
128
+
129
+ ## Community Support, Developers, & Help:
130
+
131
+ This is an actively developed package and we welcome community development and involvement.
132
+
133
+ - If you want to contribute to the code, please read our guide [here](https://github.com/DeepLabCut/DeepLabCut/blob/master/CONTRIBUTING.md), which is provided at the main repository of DeepLabCut.
134
+
135
+ - We are a community partner on the [![Image.sc forum](https://img.shields.io/badge/dynamic/json.svg?label=forum&amp;url=https%3A%2F%2Fforum.image.sc%2Ftags%2Fdeeplabcut.json&amp;query=%24.topic_list.tags.0.topic_count&amp;colorB=brightgreen&amp;&amp;suffix=%20topics&amp;logo=data:image/png;base64,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)](https://forum.image.sc/tags/deeplabcut). Please post help and support questions on the forum with the tag DeepLabCut. Check out their mission statement [Scientific Community Image Forum: A discussion forum for scientific image software](https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000340).
136
+
137
+ - If you encounter a previously unreported bug/code issue, please post here (we encourage you to search issues first): https://github.com/DeepLabCut/DeepLabCut-live/issues
138
+
139
+ - For quick discussions here: [![Gitter](https://badges.gitter.im/DeepLabCut/community.svg)](https://gitter.im/DeepLabCut/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
140
+
141
+ ### Reference:
142
+
143
+ If you utilize our tool, please [cite Kane et al, eLife 2020](https://elifesciences.org/articles/61909). The preprint is available here: https://www.biorxiv.org/content/10.1101/2020.08.04.236422v2
144
+
145
+ ```
146
+ @Article{Kane2020dlclive,
147
+ author = {Kane, Gary and Lopes, Gonçalo and Sanders, Jonny and Mathis, Alexander and Mathis, Mackenzie},
148
+ title = {Real-time, low-latency closed-loop feedback using markerless posture tracking},
149
+ journal = {eLife},
150
+ year = {2020},
151
+ }
152
+ ```
153
+
Repositories/DeepLabCut-live/benchmarking/run_dlclive_benchmark.py ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ DeepLabCut Toolbox (deeplabcut.org)
3
+ © A. & M. Mathis Labs
4
+
5
+ Licensed under GNU Lesser General Public License v3.0
6
+ """
7
+
8
+ # Script for running the official benchmark from Kane et al, 2020.
9
+ # Please share your results at https://github.com/DeepLabCut/DLC-inferencespeed-benchmark
10
+
11
+ import os, pathlib
12
+ import glob
13
+
14
+ from dlclive import benchmark_videos, download_benchmarking_data
15
+
16
+ datafolder = os.path.join(
17
+ pathlib.Path(__file__).parent.absolute(), "Data-DLC-live-benchmark"
18
+ )
19
+
20
+ if not os.path.isdir(datafolder): # only download if data doesn't exist!
21
+ # Downloading data.... this takes a while (see terminal)
22
+ download_benchmarking_data(datafolder)
23
+
24
+ n_frames = 10000 # change to 10000 for testing on a GPU!
25
+ pixels = [2500, 10000, 40000, 160000, 320000, 640000]
26
+
27
+ dog_models = glob.glob(datafolder + "/dog/*[!avi]")
28
+ dog_video = glob.glob(datafolder + "/dog/*.avi")[0]
29
+ mouse_models = glob.glob(datafolder + "/mouse_lick/*[!avi]")
30
+ mouse_video = glob.glob(datafolder + "/mouse_lick/*.avi")[0]
31
+
32
+ this_dir = os.path.dirname(os.path.realpath(__file__))
33
+ # storing results in /benchmarking/results: (for your PR)
34
+ out_dir = os.path.normpath(this_dir + "/results")
35
+
36
+ if not os.path.isdir(out_dir):
37
+ os.mkdir(out_dir)
38
+
39
+ for m in dog_models:
40
+ benchmark_videos(m, dog_video, output=out_dir, n_frames=n_frames, pixels=pixels)
41
+
42
+ for m in mouse_models:
43
+ benchmark_videos(m, mouse_video, output=out_dir, n_frames=n_frames, pixels=pixels)
Repositories/DeepLabCut-live/dlclive/__init__.py ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ DeepLabCut Toolbox (deeplabcut.org)
3
+ © A. & M. Mathis Labs
4
+
5
+ Licensed under GNU Lesser General Public License v3.0
6
+ """
7
+
8
+ from dlclive.version import __version__, VERSION
9
+ from dlclive.dlclive import DLCLive
10
+ from dlclive.processor import Processor
11
+ from dlclive.benchmark import benchmark, benchmark_videos, download_benchmarking_data
Repositories/DeepLabCut-live/dlclive/benchmark.py ADDED
@@ -0,0 +1,726 @@