FastGS/full_eval.py at main · fastgs/FastGS · GitHub

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
#
# Copyright (C) 2023, Inria
# GRAPHDECO research group, https://team.inria.fr/graphdeco
# All rights reserved.
#
# This software is free for non-commercial, research and evaluation use
# under the terms of the LICENSE.md file.
#
# For inquiries contact  george.drettakis@inria.fr
#

import os, time
from argparse import ArgumentParser

mipnerf360_outdoor_scenes = ["bicycle", "flowers", "garden", "stump", "treehill"]
mipnerf360_indoor_scenes = ["room", "counter", "kitchen", "bonsai"]
tanks_and_temples_scenes = ["truck", "train"]
deep_blending_scenes = ["drjohnson", "playroom"]

# Scene-specific budgets for "big" mode (final_count)
big_budgets = {
    "bicycle": 5987095,
    "flowers": 3618411,
    "garden": 5728191,
    "stump": 4867429,
    "treehill": 3770257,
    "room": 1548960,
    "counter": 1190919,
    "kitchen": 1803735,
    "bonsai": 1252367,
    "truck": 2584171,
    "train": 1085480,
    "playroom": 2326100,
    "drjohnson": 3273600
}

# Scene-specific budgets for "budget" mode (multiplier)
budget_multipliers = {
    "bicycle": 15,
    "flowers": 15,
    "garden": 15,
    "stump": 15,
    "treehill": 15,
    "room": 2,
    "counter": 2,
    "kitchen": 2,
    "bonsai": 2,
    "truck": 2,
    "train": 2,
    "playroom": 5,
    "drjohnson": 5
}

parser = ArgumentParser(description="Full evaluation script parameters")
parser.add_argument("--skip_training", action="store_true")
parser.add_argument("--skip_rendering", action="store_true")
parser.add_argument("--skip_metrics", action="store_true")
parser.add_argument("--output_path", default="./eval")
parser.add_argument("--mode", type=str, default="big", choices=["budget", "big"])
parser.add_argument("--optimizer_type", type=str, default="default")
parser.add_argument("--sh_lower", action="store_true")
parser.add_argument("--dry_run", action="store_true")
args, _ = parser.parse_known_args()

all_scenes = []
all_scenes.extend(mipnerf360_outdoor_scenes)
all_scenes.extend(mipnerf360_indoor_scenes)
all_scenes.extend(tanks_and_temples_scenes)
all_scenes.extend(deep_blending_scenes)

if not args.skip_training or not args.skip_rendering:
    parser.add_argument('--mipnerf360', "-m360", required=True, type=str)
    parser.add_argument("--tanksandtemples", "-tat", required=True, type=str)
    parser.add_argument("--deepblending", "-db", required=True, type=str)
    args = parser.parse_args()

def run_cmd(CMD, args):
    print(CMD)
    if not args.dry_run:
        os.system(CMD)

if not args.skip_training:
    common_args = " --quiet --eval --test_iterations -1 "
    common_args += " --optimizer_type {}".format(args.optimizer_type)

    if args.sh_lower:
        common_args += " --sh_lower"

    if args.mode == "big":
        mode_param = " --densification_interval 100 --mode final_count"
        start_time = time.time()
        for scene in mipnerf360_outdoor_scenes:
            source = args.mipnerf360 + "/" + scene
            budget_param = " --budget {} ".format(big_budgets[scene])
            CMD = "python train.py -s " + source + " -i images_4 -m " + args.output_path + "/" + f"{scene}_big" + common_args + budget_param + mode_param
            run_cmd(CMD, args)
        for scene in mipnerf360_indoor_scenes:
            source = args.mipnerf360 + "/" + scene
            budget_param = " --budget {} ".format(big_budgets[scene])
            CMD = "python train.py -s " + source + " -i images_2 -m " + args.output_path + "/" + f"{scene}_big" + common_args + budget_param + mode_param
            run_cmd(CMD, args)
        m360_timing = (time.time() - start_time)/60.0

        start_time = time.time()
        for scene in tanks_and_temples_scenes:
            source = args.tanksandtemples + "/" + scene
            budget_param = " --budget {} ".format(big_budgets[scene])
            CMD = "python train.py -s " + source + " -m " + args.output_path + "/" + f"{scene}_big" + common_args + budget_param + mode_param
            run_cmd(CMD, args)
        tandt_timing = (time.time() - start_time)/60.0

        start_time = time.time()
        for scene in deep_blending_scenes:
            source = args.deepblending  + "/" + scene
            budget_param = " --budget {} ".format(big_budgets[scene])
            CMD = "python train.py -s " + source + " -m " + args.output_path + "/" + f"{scene}_big" + common_args + budget_param + mode_param
            run_cmd(CMD, args)
        db_timing = (time.time() - start_time)/60.0

    elif args.mode == "budget":
        mode_param = " --densification_interval 500 --mode multiplier"
        start_time = time.time()
        for scene in mipnerf360_outdoor_scenes:
            source = args.mipnerf360 + "/" + scene
            budget_param = " --budget {} ".format(budget_multipliers[scene])
            CMD = "python train.py -s " + source + " -i images_4 -m " + args.output_path + "/" + f"{scene}_budget" + common_args + budget_param + mode_param
            run_cmd(CMD, args)
        for scene in mipnerf360_indoor_scenes:
            source = args.mipnerf360 + "/" + scene
            budget_param = " --budget {} ".format(budget_multipliers[scene])
            CMD = "python train.py -s " + source + " -i images_2 -m " + args.output_path + "/" + f"{scene}_budget" + common_args + budget_param + mode_param
            run_cmd(CMD, args)
        m360_timing = (time.time() - start_time)/60.0

        start_time = time.time()
        for scene in tanks_and_temples_scenes:
            source = args.tanksandtemples + "/" + scene
            budget_param = " --budget {} ".format(budget_multipliers[scene])
            CMD = "python train.py -s " + source + " -m " + args.output_path + "/" + f"{scene}_budget" + common_args + budget_param + mode_param
            run_cmd(CMD, args)
        tandt_timing = (time.time() - start_time)/60.0

        start_time = time.time()
        for scene in deep_blending_scenes:
            source = args.deepblending  + "/" + scene
            budget_param = " --budget {} ".format(budget_multipliers[scene])
            CMD = "python train.py -s " + source + " -m " + args.output_path + "/" + f"{scene}_budget" + common_args + budget_param + mode_param
            run_cmd(CMD, args)
        db_timing = (time.time() - start_time)/60.0

if not args.dry_run:
    with open(os.path.join(args.output_path, "timing.txt"), 'w') as file:
        file.write(f"m360: {m360_timing} minutes \n tandt: {tandt_timing} minutes \n db: {db_timing} minutes\n")

if not args.skip_rendering:
    if args.mode == "big":
        for scene in all_scenes:
            output_path = args.output_path + "/" + scene + "_big"
            CMD = f"python render.py -m {output_path}"
            run_cmd(CMD, args)

    elif args.mode == "budget":
        for scene in all_scenes:
            output_path = args.output_path + "/" + scene + "_budget"
            CMD = f"python render.py -m {output_path}"
            run_cmd(CMD, args)

if not args.skip_metrics:
    if args.mode == "big":
        for scene in all_scenes:
            output_path = args.output_path + "/" + scene + "_big"
            CMD = f"python metrics.py -m {output_path}"
            run_cmd(CMD, args)

    elif args.mode == "budget":
        for scene in all_scenes:
            output_path = args.output_path + "/" + scene + "_budget"
            CMD = f"python metrics.py -m {output_path}"
            run_cmd(CMD, args)