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Runtime error
Runtime error
da03
commited on
Commit
·
5c64b10
1
Parent(s):
2d9e199
- online_data_generation.py +76 -213
online_data_generation.py
CHANGED
@@ -7,14 +7,19 @@ import sqlite3
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import logging
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import cv2
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import numpy as np
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from datetime import datetime
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler("
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logging.StreamHandler()
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]
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)
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@@ -22,9 +27,10 @@ logger = logging.getLogger(__name__)
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# Define constants
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DB_FILE = "trajectory_processor.db"
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OUTPUT_DIR = "generated_videos"
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FRAMES_DIR = "interaction_logs"
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def initialize_database():
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"""Initialize the SQLite database if it doesn't exist."""
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@@ -50,8 +56,6 @@ def initialize_database():
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start_time REAL,
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end_time REAL,
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processed_time TIMESTAMP,
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video_path TEXT,
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frame_count INTEGER,
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trajectory_id INTEGER,
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UNIQUE(log_file, segment_index)
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)
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@@ -137,128 +141,7 @@ def load_trajectory(log_file):
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return []
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def
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"""Get all frame files for a client ID, sorted by timestamp."""
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frame_dir = os.path.join(FRAMES_DIR, f"frames_{client_id}")
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if not os.path.exists(frame_dir):
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logger.warning(f"No frame directory found for client {client_id}")
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return []
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frames = glob.glob(os.path.join(frame_dir, "*.png"))
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# Sort frames by timestamp in filename
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frames.sort(key=lambda x: float(os.path.basename(x).split('.png')[0]))
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return frames
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def process_trajectory(trajectory, output_file):
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"""
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Process a trajectory and create a video file.
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Args:
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trajectory: List of interaction log entries
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output_file: Path to save the output video
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Returns:
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(bool, int): (success status, frame count)
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"""
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if not trajectory:
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logger.error("Cannot process empty trajectory")
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return False, 0
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try:
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# Extract client_id from the first entry
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client_id = trajectory[0].get("client_id")
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if not client_id:
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logger.error("Trajectory missing client_id")
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return False, 0
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# Get all frame files for this client
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frame_files = get_frame_files(client_id)
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if not frame_files:
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logger.error(f"No frames found for client {client_id}")
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return False, 0
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# Read the first frame to get dimensions
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first_frame = cv2.imread(frame_files[0])
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if first_frame is None:
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logger.error(f"Could not read first frame {frame_files[0]}")
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return False, 0
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height, width, channels = first_frame.shape
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-
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# Create video writer
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fourcc = cv2.VideoWriter_fourcc(*'mp4v')
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video = cv2.VideoWriter(output_file, fourcc, 10.0, (width, height))
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# Process each frame
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for frame_file in frame_files:
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frame = cv2.imread(frame_file)
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if frame is not None:
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video.write(frame)
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# Release the video writer
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video.release()
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logger.info(f"Successfully created video {output_file} with {len(frame_files)} frames")
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return True, len(frame_files)
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except Exception as e:
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logger.error(f"Error processing trajectory: {e}")
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return False, 0
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-
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-
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def get_next_id():
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"""Get the next available ID from the database."""
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conn = sqlite3.connect(DB_FILE)
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cursor = conn.cursor()
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cursor.execute("SELECT value FROM config WHERE key = 'next_id'")
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result = cursor.fetchone()
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next_id = int(result[0])
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conn.close()
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return next_id
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-
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def increment_next_id():
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"""Increment the next ID in the database."""
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conn = sqlite3.connect(DB_FILE)
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cursor = conn.cursor()
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cursor.execute("UPDATE config SET value = value + 1 WHERE key = 'next_id'")
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conn.commit()
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conn.close()
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def is_session_processed(log_file):
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"""Check if a session has already been processed."""
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conn = sqlite3.connect(DB_FILE)
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cursor = conn.cursor()
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cursor.execute("SELECT 1 FROM processed_sessions WHERE log_file = ?", (log_file,))
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result = cursor.fetchone() is not None
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conn.close()
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return result
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def mark_session_processed(log_file, client_id, video_path, frame_count):
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"""Mark a session as processed in the database."""
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conn = sqlite3.connect(DB_FILE)
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cursor = conn.cursor()
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cursor.execute(
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"INSERT INTO processed_sessions (log_file, client_id, processed_time, video_path, frame_count) VALUES (?, ?, ?, ?, ?)",
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(log_file, client_id, datetime.now().isoformat(), video_path, frame_count)
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)
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conn.commit()
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conn.close()
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def process_session_file(log_file):
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"""
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Process a session file, splitting into multiple trajectories at reset points.
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Returns a list of successfully processed trajectory IDs.
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trajectory = load_trajectory(log_file)
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if not trajectory:
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logger.error(f"Empty trajectory for {log_file}, skipping")
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return []
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client_id = trajectory[0].get("client_id", "unknown")
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@@ -287,6 +171,7 @@ def process_session_file(log_file):
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# If no resets and no EOS, this is incomplete - skip
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if not reset_indices and not has_eos:
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logger.warning(f"Session {log_file} has no resets and no EOS, may be incomplete")
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return []
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# Split trajectory at reset points
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cursor.execute("SELECT value FROM config WHERE key = 'next_id'")
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next_id = int(cursor.fetchone()[0])
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#
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segment_label = f"segment_{i+1}_of_{len(sub_trajectories)}"
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output_file = os.path.join(OUTPUT_DIR, f"trajectory_{next_id:06d}_{segment_label}.mp4")
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# Find timestamps for this segment to get corresponding frames
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start_time = sub_traj[0]["timestamp"]
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end_time = sub_traj[-1]["timestamp"]
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# Process this sub-trajectory
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# Mark this segment as processed
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cursor.execute(
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"""INSERT INTO processed_segments
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(log_file, client_id, segment_index, start_time, end_time,
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processed_time,
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VALUES (?, ?, ?, ?, ?, ?,
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(log_file, client_id, i, start_time, end_time,
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datetime.now().isoformat(),
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)
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# Increment the next ID
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processed_ids.append(next_id)
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logger.info(f"Successfully processed segment {i+1}/{len(sub_trajectories)} from {log_file}")
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# Mark the entire session as processed
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return processed_ids
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def
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"""
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trajectory: List of interaction log entries for this segment
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output_file: Path to save the output video
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start_time: Start timestamp for this segment
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end_time: End timestamp for this segment
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Returns:
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(bool, int): (success status, frame count)
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"""
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# Filter frames to the time range of this segment
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# Frame filenames are timestamps, so we can use them for filtering
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segment_frames = [
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f for f in all_frames
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if start_time <= float(os.path.basename(f).split('.png')[0]) <= end_time
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]
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if not segment_frames:
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logger.error(f"No frames found in time range for segment {start_time}-{end_time}")
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return False, 0
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# Read the first frame to get dimensions
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first_frame = cv2.imread(segment_frames[0])
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if first_frame is None:
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logger.error(f"Could not read first frame {segment_frames[0]}")
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return False, 0
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video.release()
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except Exception as e:
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logger.error(f"Error processing trajectory segment: {e}")
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return False, 0
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def main():
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"""Main function to run the data processing pipeline."""
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# Create output directory if it doesn't exist
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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# Initialize database
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initialize_database()
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# Find all log files
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log_files = glob.glob(os.path.join(FRAMES_DIR, "session_*.jsonl"))
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logger.info(f"Found {len(log_files)} log files")
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total_trajectories = 0
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for log_file in valid_sessions:
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logger.info(f"Processing session file: {log_file}")
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processed_ids = process_session_file(log_file)
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total_trajectories += len(processed_ids)
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# Get next ID for reporting
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next_id = int(cursor.fetchone()[0])
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conn.close()
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logger.info(f"Processing complete. Generated {total_trajectories}
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logger.info(f"Next ID will be {next_id}")
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import logging
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import cv2
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import numpy as np
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import subprocess
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from datetime import datetime
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from typing import List, Dict, Any, Tuple
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# Import the existing functions
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from latent_diffusion.ldm.data.data_collection import process_trajectory, initialize_clean_state
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler("trajectory_processor.log"),
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logging.StreamHandler()
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]
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)
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# Define constants
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DB_FILE = "trajectory_processor.db"
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FRAMES_DIR = "interaction_logs"
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SCREEN_WIDTH = 512
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SCREEN_HEIGHT = 384
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MEMORY_LIMIT = "2g"
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def initialize_database():
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"""Initialize the SQLite database if it doesn't exist."""
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start_time REAL,
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end_time REAL,
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processed_time TIMESTAMP,
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trajectory_id INTEGER,
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UNIQUE(log_file, segment_index)
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)
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return []
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def process_session_file(log_file, clean_state):
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"""
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Process a session file, splitting into multiple trajectories at reset points.
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Returns a list of successfully processed trajectory IDs.
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trajectory = load_trajectory(log_file)
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if not trajectory:
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logger.error(f"Empty trajectory for {log_file}, skipping")
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conn.close()
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return []
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client_id = trajectory[0].get("client_id", "unknown")
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# If no resets and no EOS, this is incomplete - skip
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if not reset_indices and not has_eos:
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logger.warning(f"Session {log_file} has no resets and no EOS, may be incomplete")
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conn.close()
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return []
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# Split trajectory at reset points
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cursor.execute("SELECT value FROM config WHERE key = 'next_id'")
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next_id = int(cursor.fetchone()[0])
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# Find timestamps for this segment
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start_time = sub_traj[0]["timestamp"]
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end_time = sub_traj[-1]["timestamp"]
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# Process this sub-trajectory using the external function
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try:
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logger.info(f"Processing segment {i+1}/{len(sub_trajectories)} from {log_file} as trajectory {next_id}")
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# Format the trajectory as needed by process_trajectory function
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formatted_trajectory = format_trajectory_for_processing(sub_traj)
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# Call the external process_trajectory function
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args = (next_id, formatted_trajectory)
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process_trajectory(args, SCREEN_WIDTH, SCREEN_HEIGHT, clean_state, MEMORY_LIMIT)
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# Mark this segment as processed
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cursor.execute(
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"""INSERT INTO processed_segments
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(log_file, client_id, segment_index, start_time, end_time,
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processed_time, trajectory_id)
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VALUES (?, ?, ?, ?, ?, ?, ?)""",
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(log_file, client_id, i, start_time, end_time,
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datetime.now().isoformat(), next_id)
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)
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# Increment the next ID
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processed_ids.append(next_id)
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logger.info(f"Successfully processed segment {i+1}/{len(sub_trajectories)} from {log_file}")
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except Exception as e:
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logger.error(f"Failed to process segment {i+1}/{len(sub_trajectories)} from {log_file}: {e}")
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continue
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# Mark the entire session as processed only if at least one segment succeeded
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if processed_ids:
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try:
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cursor.execute(
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"INSERT INTO processed_sessions (log_file, client_id, processed_time) VALUES (?, ?, ?)",
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(log_file, client_id, datetime.now().isoformat())
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)
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246 |
+
conn.commit()
|
247 |
+
except sqlite3.IntegrityError:
|
248 |
+
# This can happen if we're re-processing a file that had some segments fail
|
249 |
+
pass
|
250 |
|
251 |
+
conn.close()
|
252 |
return processed_ids
|
253 |
|
254 |
|
255 |
+
def format_trajectory_for_processing(trajectory):
|
256 |
"""
|
257 |
+
Format the trajectory in the structure expected by process_trajectory function.
|
258 |
|
259 |
+
The exact format will depend on what your process_trajectory function expects.
|
260 |
+
This is a placeholder - modify based on the actual requirements.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
261 |
"""
|
262 |
+
formatted_events = []
|
263 |
+
|
264 |
+
for entry in trajectory:
|
265 |
+
# Skip control messages
|
266 |
+
if entry.get("is_reset") or entry.get("is_eos"):
|
267 |
+
continue
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
268 |
|
269 |
+
# Extract input data
|
270 |
+
inputs = entry.get("inputs", {})
|
271 |
+
key_events = []
|
272 |
+
for key in inputs.get("keys_down", []):
|
273 |
+
key_events.append(("keydown", key))
|
274 |
+
for key in inputs.get("keys_up", []):
|
275 |
+
key_events.append(("keyup", key))
|
276 |
+
event = {
|
277 |
+
"pos": (inputs.get("x"), inputs.get("y")),
|
278 |
+
"left_click": inputs.get("is_left_click", False),
|
279 |
+
"right_click": inputs.get("is_right_click", False),
|
280 |
+
"key_events": key_events,
|
281 |
+
}
|
|
|
282 |
|
283 |
+
formatted_events.append(event)
|
284 |
+
|
285 |
+
return formatted_events
|
|
|
|
|
|
|
286 |
|
287 |
|
288 |
def main():
|
289 |
"""Main function to run the data processing pipeline."""
|
|
|
|
|
|
|
290 |
# Initialize database
|
291 |
initialize_database()
|
292 |
|
293 |
+
# Initialize clean Docker state once
|
294 |
+
logger.info("Initializing clean container state...")
|
295 |
+
clean_state = initialize_clean_state()
|
296 |
+
logger.info(f"Clean state initialized: {clean_state}")
|
297 |
+
|
298 |
# Find all log files
|
299 |
log_files = glob.glob(os.path.join(FRAMES_DIR, "session_*.jsonl"))
|
300 |
logger.info(f"Found {len(log_files)} log files")
|
|
|
321 |
total_trajectories = 0
|
322 |
for log_file in valid_sessions:
|
323 |
logger.info(f"Processing session file: {log_file}")
|
324 |
+
processed_ids = process_session_file(log_file, clean_state)
|
325 |
total_trajectories += len(processed_ids)
|
326 |
|
327 |
# Get next ID for reporting
|
|
|
331 |
next_id = int(cursor.fetchone()[0])
|
332 |
conn.close()
|
333 |
|
334 |
+
logger.info(f"Processing complete. Generated {total_trajectories} trajectories.")
|
335 |
logger.info(f"Next ID will be {next_id}")
|
336 |
|
337 |
|