File size: 12,057 Bytes
f1caa47
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
"""Full distribution statistics for a matrix_capture.py run (clip, frame and coverage level).

usage: matrix_stats.py DATA_DIR OUT_DIR

Reads every clip's meta.json, frames.jsonl and graybox cond frames. Writes
OUT_DIR/stats.json and per map: frames-<map>.png (player frames per 2 m cell),
sectors-<map>.png (yaw sectors seen per 10 m block, 0-8).

"In view" counts living characters whose direction from the camera lies inside
the horizontal field of view (80 degrees, 70 when aiming) and within 40 m; walls
are not traced, so it is an upper bound on what is actually visible.
"""
import collections
import json
import math
import sys
from pathlib import Path

import cv2
import numpy as np

SKY_TOL = 12


def hist(values, edges):
    counts = [0] * (len(edges) - 1)
    for v in values:
        for i in range(len(edges) - 1):
            if edges[i] <= v < edges[i + 1]:
                counts[i] += 1
                break
    return counts


def share(n, d):
    return round(n / d, 4) if d else None


def forward(q):
    x, y, z, w = q
    # Rotate (0, 0, -1) by quaternion (x, y, z, w).
    return (-(2 * (x * z + w * y)), -(2 * (y * z - w * x)), -(1 - 2 * (x * x + y * y)))


def main():
    data, out = Path(sys.argv[1]), Path(sys.argv[2])
    out.mkdir(parents=True, exist_ok=True)
    stats = {}
    for map_id in ('paris', 'tsinghua'):
        clips = sorted(c for c in (data / map_id).glob('clip_*') if (c / 'meta.json').exists())
        metas = [json.loads((c / 'meta.json').read_text()) for c in clips]
        c = collections.Counter
        clip = dict(
            clips=len(metas), frames_per_clip=metas[0]['frames'], fps=metas[0]['fps'],
            teams=dict(sorted(c(f"{m['teams'][0]}v{m['teams'][1]}" for m in metas).items())),
            characters=dict(sorted(c(m['teams'][0] + m['teams'][1] for m in metas).items())),
            distance=dict(c(m['distance'] for m in metas if m['teams'][1])),
            side=dict(c(m['side'] for m in metas if m['teams'][1])),
            pitch_tier=dict(sorted(c(str(m['pitch_bias']) for m in metas).items())),
            anchors=dict(c(m['anchor'] or 'block' for m in metas).most_common()),
            start_yaw_sector=hist([(m['setup']['player']['yaw'] % (2 * math.pi)) / (math.pi / 4) for m in metas], list(range(9))),
            teams_by_distance={d: dict(sorted(c(f"{m['teams'][0]}v{m['teams'][1]}" for m in metas if m['distance'] == d and m['teams'][1]).items()))
                               for d in ('close', 'mid', 'far')},
            max_drift=max(m['max_drift'] for m in metas),
            kills_per_clip=dict(sorted(c(m['kills'] for m in metas if m['teams'][1]).items())),
            player_shots_per_clip=hist([m['shots'] for m in metas if m['teams'][1]], [0, 1, 10, 20, 30, 40, 1000]),
            player_hit_rate=share(sum(m['hits'] for m in metas), sum(m['shots'] for m in metas)),
            wall_s_mean=round(float(np.mean([m['wall_s'] for m in metas])), 1))
        frames = collections.Counter()
        yaw_frames, pitch_frames, cam_dist, near_enemy, in_view_enemy, in_view_any = [], [], [], [], [], []
        cells, sectors, block_frames = collections.Counter(), collections.defaultdict(set), collections.Counter()
        refills, respawns, displacement = 0, 0, []
        sky_clip = []
        top = collections.Counter()
        for cdir, m in zip(clips, metas):
            fight = m['teams'][1] > 0
            prev, start, last = None, None, None
            for line in (cdir / 'frames.jsonl').read_text().splitlines():
                row = json.loads(line)
                s, inp, cam = row['state'], row['input'], row['camera']
                p = s['player']
                frames['total'] += 1
                frames['fight'] += fight
                held = set(inp['down'])
                frames['bullets'] += s['bullets'] > 0
                frames['fight_bullets'] += fight and s['bullets'] > 0
                frames['grenade_flying'] += s['grenades'] > 0
                frames['reloading'] += s['reloading'] > 0
                frames[f"weapon{s['weapon']}"] += 1
                frames['avatar_hidden'] += not cam['v']
                start = start or (p['x'], p['z'])
                last = (p['x'], p['z'])
                yaw_frames.append((s['yaw'] % (2 * math.pi)) / (math.pi / 4))
                pitch_frames.append(s['pitch'])
                if cam['s']:
                    cam_dist.append(cam['s']['distance'])
                cells[(math.floor(p['x'] / 2), math.floor(p['z'] / 2))] += 1
                block = (math.floor(p['x'] / 10), math.floor(p['z'] / 10))
                block_frames[block] += 1
                sectors[block].add(int((s['yaw'] % (2 * math.pi)) / (math.pi / 4)) % 8)
                if prev:
                    if p['health'] > prev['player']['health'] + 50:
                        refills += 1
                    respawns += sum(1 for a, b in zip(s['actors'], prev['actors']) if a['alive'] and not b['alive'])
                # Who is in front of the camera (three.js frame: z = -nav z).
                fx, fy, fz = forward(cam['q'])
                horiz = math.hypot(fx, fz) or 1
                half = math.radians(cam['fov'] * 960 / 544 / 2) if False else math.radians(40)
                cx, cz = cam['p'][0], cam['p'][2]
                seen_enemy = seen_any = 0
                dists = []
                for a in s['actors']:
                    if not a['alive']:
                        continue
                    ax, az = a['x'], -a['z']
                    dx, dz = ax - cx, az - cz
                    d = math.hypot(dx, dz)
                    if a['team'] == 1:
                        dists.append(math.hypot(a['x'] - p['x'], a['z'] - p['z']))
                    if d < 40 and d > .3:
                        cos = (dx * fx + dz * fz) / (d * horiz)
                        if cos > math.cos(half):
                            seen_any += 1
                            seen_enemy += a['team'] == 1
                if fight:
                    in_view_enemy.append(seen_enemy)
                    if dists:
                        near_enemy.append(min(dists))
                in_view_any.append(seen_any)
                for k in ('j', 'k', 'c', 'w', 'a', 's', 'd'):
                    frames[f'key_{k}'] += k in held or (prev is not None and k in prev['held'])
                for k in ('shift', ' ', 'f', 'r', '1', '2', '3'):
                    frames[f'tap_{k}'] += k in inp['down']
                prev = dict(row['state'], held=held | (prev['held'] - set(inp['up']) if prev else set()))
            displacement.append(math.hypot(last[0] - start[0], last[1] - start[1]))
            # Graybox ground check: share of the bottom third that is sky colour.
            shares = []
            for l in (0, 15, 30, 45, 59):
                im = cv2.imread(str(cdir / 'cond' / f'{l:06d}.png'))
                if im is None:
                    continue
                if len(top) < 2000:
                    top.update(map(tuple, im[0, ::40].tolist()))
                shares.append(im)
            sky_clip.append(shares)
        sky = np.array(top.most_common(1)[0][0])
        sky_share = []
        for images in sky_clip:
            vals = [float((np.abs(im[2 * im.shape[0] // 3:].astype(int) - sky).sum(-1) < SKY_TOL).mean()) for im in images]
            sky_share.append(float(np.mean(vals)) if vals else 0.0)
        n = frames['total']
        sector_counts = [len(v) for v in sectors.values()]
        bf = sorted(block_frames.values())
        frame = dict(
            frames=n, fight_frames=frames['fight'],
            yaw_sector_frame_share=[share(x, n) for x in hist(yaw_frames, list(range(9)))],
            pitch_hist=dict(zip(['<-0.3', '-0.3~-0.1', '-0.1~0.05', '0.05~0.2', '>=0.2'],
                                [share(x, n) for x in hist(pitch_frames, [-9, -.3, -.1, .05, .2, 9])])),
            camera_distance_hist=dict(zip(['<1.15 (avatar hidden)', '1.15~2.4', '2.4~4', '>=4'],
                                          [share(x, len(cam_dist)) for x in hist(cam_dist, [0, 1.15, 2.4, 4, 99])])),
            blocks_visited=len(sectors), block_frames_min_median_max=[bf[0], bf[len(bf) // 2], bf[-1]],
            blocks_by_yaw_sectors=dict(sorted(collections.Counter(sector_counts).items())),
            blocks_all_8_sectors=share(sum(x == 8 for x in sector_counts), len(sector_counts)),
            cells_2m_visited=len(cells),
            fight_frames_with_bullets=share(frames['fight_bullets'], frames['fight']),
            fight_enemies_in_view=dict(zip(['0', '1', '2', '3', '4+'], [share(x, len(in_view_enemy)) for x in hist(in_view_enemy, [0, 1, 2, 3, 4, 99])])),
            characters_in_view=dict(zip(['0', '1', '2', '3', '4+'], [share(x, len(in_view_any)) for x in hist(in_view_any, [0, 1, 2, 3, 4, 99])])),
            nearest_enemy_m=dict(zip(['<5', '5~10', '10~20', '20~35', '>=35'], [share(x, len(near_enemy)) for x in hist(near_enemy, [0, 5, 10, 20, 35, 999])])),
            fire_held=share(frames['key_j'], n), aim_held=share(frames['key_k'], n), crouch=share(frames['key_c'], n),
            move_w=share(frames['key_w'], n), strafe=share(frames['key_a'] + frames['key_d'], n), back_s=share(frames['key_s'], n),
            reloading=share(frames['reloading'], n), grenade_in_air=share(frames['grenade_flying'], n),
            weapon_share={'pistol': share(frames['weapon0'], n), 'rifle': share(frames['weapon1'], n), 'shotgun': share(frames['weapon2'], n)},
            avatar_hidden=share(frames['avatar_hidden'], n),
            events_per_clip={'dash': round(frames['tap_shift'] / len(metas), 2), 'jump': round(frames['tap_ '] / len(metas), 2),
                             'grenade': round(frames['tap_f'] / len(metas), 2), 'reload_key': round(frames['tap_r'] / len(metas), 2),
                             'weapon_switch': round((frames['tap_1'] + frames['tap_2'] + frames['tap_3']) / len(metas), 2),
                             'bot_respawn': round(respawns / len(metas), 2), 'player_refill': round(refills / len(metas), 2)},
            displacement_m=dict(zip(['<5', '5~15', '15~30', '>=30'], hist(displacement, [0, 5, 15, 30, 999]))),
            graybox_sky_bottom_third=dict(mean=round(float(np.mean(sky_share)), 3),
                                          clips=dict(zip(['<10%', '10~30%', '30~50%', '>=50%'], hist(sky_share, [0, .1, .3, .5, 1.01])))))
        stats[map_id] = dict(clip=clip, frame=frame)
        # Maps: frames per 2 m cell, and yaw sectors per 10 m block.
        xs = [k[0] for k in cells]
        zs = [k[1] for k in cells]
        grid = np.zeros((max(zs) - min(zs) + 1, max(xs) - min(xs) + 1))
        for (x, z), v in cells.items():
            grid[z - min(zs), x - min(xs)] = v
        norm = np.log1p(grid) / np.log1p(grid).max()
        image = cv2.applyColorMap((norm * 255).astype(np.uint8), cv2.COLORMAP_VIRIDIS)
        image[grid == 0] = (245, 245, 245)
        cv2.imwrite(str(out / f'frames-{map_id}.png'), cv2.resize(image[::-1], None, fx=6, fy=6, interpolation=cv2.INTER_NEAREST))
        bx = [k[0] for k in sectors]
        bz = [k[1] for k in sectors]
        sec = np.full((max(bz) - min(bz) + 1, max(bx) - min(bx) + 1), -1)
        for (x, z), v in sectors.items():
            sec[z - min(bz), x - min(bx)] = len(v)
        image = cv2.applyColorMap((np.clip(sec, 0, 8) * 31).astype(np.uint8), cv2.COLORMAP_VIRIDIS)
        image[sec < 0] = (245, 245, 245)
        image = cv2.resize(image[::-1], None, fx=30, fy=30, interpolation=cv2.INTER_NEAREST)
        for (x, z), v in sectors.items():
            row = sec.shape[0] - 1 - (z - min(bz))
            cv2.putText(image, str(len(v)), ((x - min(bx)) * 30 + 9, row * 30 + 21), 0, .5, (255, 255, 255) if len(v) < 6 else (0, 0, 0), 1)
        cv2.imwrite(str(out / f'sectors-{map_id}.png'), image)
        print(map_id, 'done', flush=True)
    (out / 'stats.json').write_text(json.dumps(stats, indent=1, ensure_ascii=False))
    print(json.dumps(stats, ensure_ascii=False))


if __name__ == '__main__':
    main()