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Video analysis on cropped videos: bug fixes for extract_outlier_frames and create_video_with_all_detections #2538

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Merged
MMathisLab merged 2 commits into from
Mar 19, 2024
Merged

Video analysis on cropped videos: bug fixes for extract_outlier_frames and create_video_with_all_detections #2538

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c08b367
get cropping parameters from metadata
n-poulsen Mar 13, 2024
2ea9673
improved code resilience
n-poulsen Mar 13, 2024
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9 changes: 9 additions & 0 deletions deeplabcut/refine_training_dataset/outlier_frames.py
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Original file line number Diff line number Diff line change
Expand Up @@ -390,11 +390,20 @@ def extract_outlier_frames(
df, dataname, _, _ = auxiliaryfunctions.load_analyzed_data(
videofolder, vname, DLCscorer, track_method=track_method
)
metadata = auxiliaryfunctions.load_video_metadata(
videofolder, vname, DLCscorer
)
nframes = len(df)
startindex = max([int(np.floor(nframes * cfg["start"])), 0])
stopindex = min([int(np.ceil(nframes * cfg["stop"])), nframes])
Index = np.arange(stopindex - startindex) + startindex

# offset if the data was cropped
if metadata.get("data", {}).get("cropping"):
x1, _, y1, _ = metadata["data"]["cropping_parameters"]
df.iloc[:, df.columns.get_level_values(level="coords") == "x"] += x1
df.iloc[:, df.columns.get_level_values(level="coords") == "y"] += y1

df = df.iloc[Index]
mask = df.columns.get_level_values("bodyparts").isin(bodyparts)
df_temp = df.loc[:, mask]
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13 changes: 7 additions & 6 deletions deeplabcut/utils/make_labeled_video.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1088,11 +1088,17 @@ def create_video_with_all_detections(
video_name = str(Path(video).stem)
print("Creating labeled video for ", video_name)
h5file = full_pickle.replace("_full.pickle", ".h5")
data, _ = auxfun_multianimal.LoadFullMultiAnimalData(h5file)
data, metadata = auxfun_multianimal.LoadFullMultiAnimalData(h5file)
data = dict(
data
) # Cast to dict (making a copy) so items can safely be popped

x1, y1 = 0, 0
if cropping is not None:
x1, _, y1, _ = cropping
elif metadata.get("data", {}).get("cropping"):
x1, _, y1, _ = metadata["data"]["cropping_parameters"]

header = data.pop("metadata")
all_jointnames = header["all_joints_names"]

Expand All @@ -1116,11 +1122,6 @@ def create_video_with_all_detections(
clip = vp(fname=video, sname=outputname, codec="mp4v")
ny, nx = clip.height(), clip.width()

x1 = 0
y1 = 0
if cropping is not None:
x1, _, y1, _ = cropping

for n in trange(clip.nframes):
frame = clip.load_frame()
if frame is None:
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