File size: 8,690 Bytes
eecfaf7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
"""
Cache all play clock readings for the OSU vs Tenn video.

This script:
1. Loads the template library
2. Reads play clock values from fixed regions for every frame (sampled at 0.5s)
3. Caches the results as JSON
4. Identifies all 40→25 transitions for timeout tracker testing

Usage:
    python scripts/cache_playclock_readings.py
"""

import json
import logging
import sys
import time
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple

import cv2
import numpy as np

# Add src to path
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))

from readers import ReadPlayClock
from setup import DigitTemplateLibrary

logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
logger = logging.getLogger(__name__)


def seconds_to_timestamp(seconds: float) -> str:
    """Convert seconds to timestamp string (H:MM:SS)."""
    hours = int(seconds // 3600)
    minutes = int((seconds % 3600) // 60)
    secs = int(seconds % 60)
    if hours > 0:
        return f"{hours}:{minutes:02d}:{secs:02d}"
    return f"{minutes}:{secs:02d}"


def cache_playclock_readings(
    video_path: str,
    template_dir: str,
    output_path: str,
    playclock_coords: Tuple[int, int, int, int],
    sample_interval: float = 0.5,
    start_time: float = 0.0,
    end_time: Optional[float] = None,
) -> Dict[str, Any]:
    """
    Cache all play clock readings for a video.

    Args:
        video_path: Path to video file
        template_dir: Path to digit templates directory
        output_path: Path to save cached readings
        playclock_coords: (x, y, width, height) absolute coordinates
        sample_interval: Seconds between samples (default 0.5)
        start_time: Start time in seconds
        end_time: End time in seconds (None for full video)

    Returns:
        Dictionary with cached readings and transitions
    """
    # Load template library
    logger.info("Loading template library from %s", template_dir)
    library = DigitTemplateLibrary()
    if not library.load(template_dir):
        raise RuntimeError(f"Failed to load templates from {template_dir}")

    coverage = library.get_coverage_status()
    logger.info("Template coverage: %d/%d (complete: %s)", coverage["total_have"], coverage["total_needed"], coverage["is_complete"])

    # Create play clock reader
    reader = ReadPlayClock(library, region_width=playclock_coords[2], region_height=playclock_coords[3])

    # Open video
    cap = cv2.VideoCapture(video_path)
    if not cap.isOpened():
        raise RuntimeError(f"Failed to open video: {video_path}")

    fps = cap.get(cv2.CAP_PROP_FPS)
    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    duration = total_frames / fps

    if end_time is None:
        end_time = duration

    logger.info("Video: %s", video_path)
    logger.info("  FPS: %.2f, Total frames: %d, Duration: %s", fps, total_frames, seconds_to_timestamp(duration))
    logger.info("  Processing: %s to %s", seconds_to_timestamp(start_time), seconds_to_timestamp(end_time))
    logger.info("  Play clock region: (%d, %d, %d, %d)", *playclock_coords)

    # Cache readings
    readings: List[Dict[str, Any]] = []
    current_time = start_time
    frames_processed = 0
    t_start = time.perf_counter()

    while current_time <= end_time:
        frame_num = int(current_time * fps)
        cap.set(cv2.CAP_PROP_POS_FRAMES, frame_num)
        ret, frame = cap.read()

        if not ret:
            current_time += sample_interval
            continue

        # Read play clock using fixed coordinates
        result = reader.read_from_fixed_location(frame, playclock_coords)

        reading_entry = {
            "timestamp": current_time,
            "frame_num": frame_num,
            "detected": result.detected,
            "value": result.value,
            "confidence": result.confidence,
            "method": result.method,
        }
        readings.append(reading_entry)

        frames_processed += 1
        current_time += sample_interval

        # Progress log every 5 minutes of video
        if frames_processed % int(300 / sample_interval) == 0:
            elapsed = time.perf_counter() - t_start
            video_minutes = current_time / 60
            logger.info("  Processed %d frames (%.1f min), elapsed: %.1fs", frames_processed, video_minutes, elapsed)

    cap.release()

    elapsed = time.perf_counter() - t_start
    logger.info("Processed %d frames in %.1fs (%.1f fps)", frames_processed, elapsed, frames_processed / elapsed)

    # Identify 40→25 transitions
    transitions = find_40_to_25_transitions(readings)
    logger.info("Found %d potential 40→25 transitions", len(transitions))

    # Build result
    result = {
        "video": Path(video_path).name,
        "config": {
            "playclock_coords": list(playclock_coords),
            "sample_interval": sample_interval,
            "start_time": start_time,
            "end_time": end_time,
        },
        "stats": {
            "total_readings": len(readings),
            "detected_readings": sum(1 for r in readings if r["detected"]),
            "processing_time": elapsed,
        },
        "readings": readings,
        "transitions_40_to_25": transitions,
    }

    # Save to file
    output_file = Path(output_path)
    output_file.parent.mkdir(parents=True, exist_ok=True)
    with open(output_file, "w", encoding="utf-8") as f:
        json.dump(result, f, indent=2)

    logger.info("Saved cache to %s", output_path)

    return result


def find_40_to_25_transitions(readings: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """
    Find all 40→25 clock transitions in the readings.

    A transition is identified when:
    1. Previous reading was 40 (or no previous reading)
    2. Current reading is 25

    Args:
        readings: List of clock readings

    Returns:
        List of transition events with timestamps and context
    """
    transitions = []
    prev_value = None
    prev_timestamp = None

    for i, reading in enumerate(readings):
        if not reading["detected"] or reading["value"] is None:
            continue

        curr_value = reading["value"]
        curr_timestamp = reading["timestamp"]

        # Check for 40→25 transition
        if prev_value == 40 and curr_value == 25:
            transition = {
                "index": i,
                "timestamp": curr_timestamp,
                "timestamp_str": seconds_to_timestamp(curr_timestamp),
                "prev_timestamp": prev_timestamp,
                "prev_value": prev_value,
                "curr_value": curr_value,
            }
            transitions.append(transition)
            logger.debug("Found 40→25 transition at %s (index %d)", seconds_to_timestamp(curr_timestamp), i)

        prev_value = curr_value
        prev_timestamp = curr_timestamp

    return transitions


def print_transitions_summary(cache_file: str) -> None:
    """Print a summary of transitions from a cache file."""
    with open(cache_file, "r", encoding="utf-8") as f:
        data = json.load(f)

    transitions = data.get("transitions_40_to_25", [])

    print("\n" + "=" * 80)
    print("40→25 CLOCK TRANSITIONS")
    print("=" * 80)
    print(f"Total transitions found: {len(transitions)}")
    print("-" * 80)
    print(f"{'#':<4} {'Timestamp':<12} {'Prev→Curr':<12} {'Index':<8}")
    print("-" * 80)

    for i, t in enumerate(transitions, 1):
        print(f"{i:<4} {t['timestamp_str']:<12} {t['prev_value']}{t['curr_value']:<8} {t['index']:<8}")

    print("=" * 80)


def main():
    """Main function to cache play clock readings."""
    # Configuration
    video_path = "full_videos/OSU vs Tenn 12.21.24.mkv"
    template_dir = "output/debug/digit_templates"
    output_path = "output/cache/playclock_readings_full.json"

    # Play clock absolute coordinates (scorebug_x + offset_x, scorebug_y + offset_y, width, height)
    # From config: scorebug (131, 972), offset (899, 18), size (51, 28)
    playclock_coords = (131 + 899, 972 + 18, 51, 28)

    # Process full video
    result = cache_playclock_readings(
        video_path=video_path,
        template_dir=template_dir,
        output_path=output_path,
        playclock_coords=playclock_coords,
        sample_interval=0.5,  # Match pipeline interval
    )

    # Print summary
    print_transitions_summary(output_path)

    # Also print detection rate
    stats = result["stats"]
    detection_rate = stats["detected_readings"] / stats["total_readings"] * 100
    print(f"\nDetection rate: {stats['detected_readings']}/{stats['total_readings']} ({detection_rate:.1f}%)")


if __name__ == "__main__":
    main()