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Prevent pandas overflow and runtime errors from division by zero/NaN (#12591)

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* Prevent pandas overflow and runtime errors from division by zero/NaN

* remove pysqlite3
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Josh Hawkins 2024-07-24 09:58:42 -05:00 committed by GitHub
parent d28ad0f0c8
commit 6de426c697
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1 changed files with 8 additions and 6 deletions
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frigate/api/review.py
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@ -475,7 +475,7 @@ def motion_activity():
logger.warning("No motion data found for the requested time range") logger.warning("No motion data found for the requested time range")
return jsonify([]) return jsonify([])
df = df.astype(dtype={"motion": "float16"}) df = df.astype(dtype={"motion": "float32"})
# set date as datetime index # set date as datetime index
df["start_time"] = pd.to_datetime(df["start_time"], unit="s") df["start_time"] = pd.to_datetime(df["start_time"], unit="s")
@ -497,11 +497,13 @@ def motion_activity():
for i in range(0, length, chunk): for i in range(0, length, chunk):
part = df.iloc[i : i + chunk] part = df.iloc[i : i + chunk]
df.iloc[i : i + chunk, 0] = ( min_val, max_val = part["motion"].min(), part["motion"].max()
(part["motion"] - part["motion"].min()) if min_val != max_val:
/ (part["motion"].max() - part["motion"].min()) df.iloc[i : i + chunk, 0] = (
* 100 part["motion"].sub(min_val).div(max_val - min_val).mul(100).fillna(0)
).fillna(0.0) )
else:
df.iloc[i : i + chunk, 0] = 0.0
# change types for output # change types for output
df.index = df.index.astype(int) // (10**9) df.index = df.index.astype(int) // (10**9)