Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
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Video editing with ffmpeg including cutting, trimming, concatenating segments, and re-encoding. Use when working with video files (.mp4, .mkv, .avi) for: removing segments, joining clips, extracting portions, or any video manipulation task.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
# Extract from start_time to end_time
ffmpeg -i input.mp4 -ss START -to END -c copy output.mp4
# With re-encoding for frame-accurate cuts
ffmpeg -i input.mp4 -ss START -to END -c:v libx264 -c:a aac output.mp4
To remove a segment, split into parts and concatenate:
# 1. Extract before the cut
ffmpeg -i input.mp4 -to CUT_START -c copy part1.mp4
# 2. Extract after the cut
ffmpeg -i input.mp4 -ss CUT_END -c copy part2.mp4
# 3. Concatenate
ffmpeg -f concat -safe 0 -i filelist.txt -c copy output.mp4
Create a file list (segments.txt):
file 'segment1.mp4'
file 'segment2.mp4'
file 'segment3.mp4'
Then concatenate:
ffmpeg -f concat -safe 0 -i segments.txt -c copy output.mp4
ffmpeg -i seg1.mp4 -i seg2.mp4 -i seg3.mp4 \
-filter_complex "[0:v][0:a][1:v][1:a][2:v][2:a]concat=n=3:v=1:a=1[v][a]" \
-map "[v]" -map "[a]" output.mp4
For removing many short segments (like filler words), the efficient approach:
import subprocess
import os
def remove_segments(input_file, segments_to_remove, output_file):
"""
segments_to_remove: list of (start, end) tuples in seconds
"""
# Get video duration
result = subprocess.run([
'ffprobe', '-v', 'error', '-show_entries', 'format=duration',
'-of', 'default=noprint_wrappers=1:nokey=1', input_file
], capture_output=True, text=True)
duration = float(result.stdout.strip())
# Sort segments and merge overlapping
segments = sorted(segments_to_remove)
# Calculate keep segments (gaps between remove segments)
keep_segments = []
current_pos = 0.0
for start, end in segments:
if start > current_pos:
keep_segments.append((current_pos, start))
current_pos = max(current_pos, end)
if current_pos < duration:
keep_segments.append((current_pos, duration))
# Extract each keep segment
temp_files = []
for i, (start, end) in enumerate(keep_segments):
temp_file = f'/tmp/seg_{i:04d}.mp4'
subprocess.run([
'ffmpeg', '-y', '-i', input_file,
'-ss', str(start), '-to', str(end),
'-c', 'copy', temp_file
], check=True)
temp_files.append(temp_file)
# Create concat list
list_file = '/tmp/concat_list.txt'
with open(list_file, 'w') as f:
for temp_file in temp_files:
f.write(f"file '{temp_file}'\n")
# Concatenate
subprocess.run([
'ffmpeg', '-y', '-f', 'concat', '-safe', '0',
'-i', list_file, '-c', 'copy', output_file
], check=True)
# Cleanup
for f in temp_files:
os.remove(f)
os.remove(list_file)
-c copy only when cutting at keyframes-c:v libx264 -c:a aacffprobe -v error -show_entries format=duration -of default=noprint_wrappers=1:nokey=1 input.mp4
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Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
中文简介正在准备中。当前显示原文说明。
AC branch pi-model power flow equations (P/Q and |S|) with transformer tap ratio and phase shift, matching `acopf-math-model.md` and MATPOWER branch fields. Use when computing branch flows in either direction, aggregating bus injections for nodal balance, checking MVA (rateA) limits, computing branch loading %, or debugging sign/units issues in AC power flow.
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Redact text from PDF documents for blind review anonymization
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Use when checking simplified ADA-derived plan-view bathroom accessibility constraints such as turning space, door clear width, toilet centerline, grab bars, and lavatory knee/toe clearance.
中文简介正在准备中。当前显示原文说明。
Analyze failed GitHub Action jobs for a pull request.
中文简介正在准备中。当前显示原文说明。
Use when extracting plan-view architectural geometry from DXF files with semantic CAD layers, especially when outputs must normalize rooms, doors, fixtures, clearances, and grab bars into machine-checkable JSON.
中文简介正在准备中。当前显示原文说明。