File size: 10,658 Bytes
382733a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
269
import os
import json
from subprocess import call, DEVNULL
import numpy as np
import shutil
import multiprocessing as mp
from lib.util.render import _install_blender, sphere_hammersley_sequence, BLENDER_PATH

try:
    mp.set_start_method("spawn", force=False)
except RuntimeError:
    pass

def _get_optimal_threads(num_workers):
    """Calculate optimal CPU threads per Blender instance."""
    total_cores = os.cpu_count() or 4
    # Reserve 1 core for system/orchestration if possible
    available_cores = max(1, total_cores - 1)
    # Distribute remaining cores among workers
    threads = max(1, available_cores // num_workers)
    # Cap at 4 threads per instance since we are GPU bound anyway 
    # and too many threads just adds contention
    return min(threads, 4)

def _render_views_chunk(file_path, chunk_output_folder, views_chunk, blender_render_engine, cuda_device_id=None, threads=None):
    """Render a subset of views into a chunk-specific folder."""
    os.makedirs(chunk_output_folder, exist_ok=True)

    # Prepare environment with GPU selection if provided
    env = os.environ.copy()
    if cuda_device_id is not None:
        env["CUDA_VISIBLE_DEVICES"] = str(cuda_device_id)

    blender_exec = env.get('BLENDER_HOME', BLENDER_PATH)
    if not os.path.exists(blender_exec) and blender_exec == BLENDER_PATH:
        blender_exec = 'blender' # Fallback if specific path missing

    output_root = os.path.dirname(os.path.dirname(chunk_output_folder))
    blender_cache_dir = os.path.join(output_root, "blender_cache")
    os.makedirs(blender_cache_dir, exist_ok=True)
    env["XDG_CACHE_HOME"] = blender_cache_dir

    args = [
        blender_exec, '-b',
        '-P', os.path.join(os.getcwd(), 'third_party/TRELLIS/dataset_toolkits', 'blender_script', 'render.py'),
        '--',
        '--views', json.dumps(views_chunk),
        '--object', os.path.expanduser(file_path),
        '--resolution', '512',
        '--output_folder', chunk_output_folder,
        '--engine', blender_render_engine,
        '--save_mesh',
    ]
    
    if threads:
        args.extend(['--threads', str(threads)])
        
    if file_path.endswith('.blend'):
        args.insert(1, file_path)

    call(args, stdout=DEVNULL, stderr=DEVNULL, env=env)

def _merge_blender_chunks(output_folder, chunk_infos, file_path, blender_render_engine):
    """Merge chunk_* folders into the main output_folder and write transforms.json."""
    frames = []
    mesh_copied = False

    for i, (chunk_path, chunk_views) in enumerate(chunk_infos):
        if not os.path.isdir(chunk_path):
            continue

        # Copy mesh.ply once (from first chunk that has it)
        mesh_src = os.path.join(chunk_path, "mesh.ply")
        mesh_dst = os.path.join(output_folder, "mesh.ply")
        if not mesh_copied and os.path.exists(mesh_src):
            shutil.copy2(mesh_src, mesh_dst)
            mesh_copied = True

        chunk_transforms_path = os.path.join(chunk_path, "transforms.json")
        
        # Simple retry logic if chunk failed
        if not os.path.exists(chunk_transforms_path):
            print(f"[merge_chunks] Warning: missing transforms.json in {chunk_path}, re-rendering chunk.")
            shutil.rmtree(chunk_path, ignore_errors=True)
            # Use default 1 thread for retry to be safe
            _render_views_chunk(file_path, chunk_path, chunk_views, blender_render_engine, threads=2)
        
        if not os.path.exists(chunk_transforms_path):
            # If still missing, raise error
            raise RuntimeError(f"Unable to generate transforms.json for {chunk_path}")
            
        with open(chunk_transforms_path, "r") as f:
            chunk_data = json.load(f)
            chunk_frames = chunk_data.get("frames", [])
        
        if not chunk_frames:
             # Empty frames could mean render failure
             raise RuntimeError(f"No frames found in {chunk_transforms_path}")

        frame_lookup = {
            os.path.basename(frame.get("file_path", "")): frame for frame in chunk_frames
        }

        for img_name in os.listdir(chunk_path):
            if not img_name.lower().endswith((".png", ".jpg", ".jpeg")):
                continue

            src = os.path.join(chunk_path, img_name)
            if img_name not in frame_lookup:
                print(f"[merge_chunks] Warning: no metadata for {img_name} in {chunk_transforms_path}, skipping image.")
                os.remove(src)
                continue

            # Rename to avoid collisions if needed, though chunks are distinct
            # Use chunk index prefix
            dst_name = f"chunk{i:02d}_{img_name}"
            dst = os.path.join(output_folder, dst_name)
            shutil.move(src, dst)

            frame = frame_lookup[img_name].copy()
            frame["file_path"] = dst_name
            frames.append(frame)

        shutil.rmtree(chunk_path)

    if not frames:
        raise RuntimeError("No frames were merged when building transforms.json")

    transforms_path = os.path.join(output_folder, "transforms.json")
    with open(transforms_path, "w") as f:
        json.dump({"frames": frames}, f, indent=4)

def _run_single_render(file_path, output_folder, views, blender_render_engine):
    # For single render, we can use more CPU threads since we are the only process
    threads = min(os.cpu_count() or 4, 8)

    output_root = os.path.dirname(output_folder)
    blender_cache_dir = os.path.join(output_root, "blender_cache")
    os.makedirs(blender_cache_dir, exist_ok=True)
    env = os.environ.copy()
    env["XDG_CACHE_HOME"] = blender_cache_dir

    blender_exec = os.environ.get('BLENDER_HOME', BLENDER_PATH)
    if not os.path.exists(blender_exec) and blender_exec == BLENDER_PATH:
        blender_exec = 'blender' # Fallback

    args = [
        # 'xvfb-run',
        # "-s", "-screen 0 1920x1080x24",
        blender_exec, '-b',
        '-P', os.path.join(os.getcwd(), 'third_party/TRELLIS/dataset_toolkits', 'blender_script', 'render.py'),
        '--',
        '--views', json.dumps(views),
        '--object', os.path.expanduser(file_path),
        '--resolution', '512',
        '--output_folder', output_folder,
        '--engine', blender_render_engine,
        '--save_mesh',
        '--threads', str(threads)
    ]
    if file_path.endswith('.blend'):
        args.insert(1, file_path)

    # call(args, stdout=DEVNULL, stderr=DEVNULL)
    call(args, env=env)


def render_all_views(file_path, output_folder, num_views=150, blender_render_engine="CYCLES", num_workers=None):
    _install_blender()
    # Build camera {yaw, pitch, radius, fov}
    yaws = []
    pitchs = []
    offset = (np.random.rand(), np.random.rand())
    for i in range(num_views):
        y, p = sphere_hammersley_sequence(i, num_views, offset)
        yaws.append(y)
        pitchs.append(p)
    radius = [2] * num_views
    fov = [40 / 180 * np.pi] * num_views
    views = [{'yaw': y, 'pitch': p, 'radius': r, 'fov': f} for y, p, r, f in zip(yaws, pitchs, radius, fov)]

    # Determine GPU availability using torch if available (safe check)
    num_gpus = 0
    try:
        import torch
        if torch.cuda.is_available():
            num_gpus = torch.cuda.device_count()
    except ImportError:
        pass
    
    # Smart worker count logic
    if num_workers is None:
        if blender_render_engine == 'CYCLES':
            if num_gpus > 0:
                # To maximize VRAM usage and overlap CPU preparation with GPU rendering,
                # we can run multiple concurrent Blender instances per GPU.
                # For object-level scenes, 2-3 workers per GPU is usually the sweet spot.
                # Too many will cause context thrashing; too few leaves VRAM idle.
                WORKERS_PER_GPU = 3
                num_workers = num_gpus * WORKERS_PER_GPU
            else:
                # No GPU found: fallback to CPU. Parallelizing CPU might help if RAM permits.
                # Cap at 4 to be safe.
                num_workers = min(os.cpu_count() or 4, 4)
        else:
             # For non-cycles (e.g. Eevee), we can be slightly more aggressive but still bound by GPU
             if num_gpus > 0:
                 num_workers = num_gpus
             else:
                 num_workers = min(os.cpu_count() or 4, 8)
    
    # Override: Force serial for small batches to avoid startup overhead
    # 15 views is small enough that overhead of 2+ processes > gain
    if len(views) < 30:
        num_workers = 1
    
    if num_workers > 1:
        print(f"[render_all_views] Running with {num_workers} workers (GPUs detected: {num_gpus}).")
    else:
        print(f"[render_all_views] Running serially (GPUs detected: {num_gpus}).")

    if num_workers <= 1:
        _run_single_render(file_path, output_folder, views, blender_render_engine)
    else:
        # Multi-process: split views into chunks and render in parallel
        num_workers = min(num_workers, num_views)
        view_chunks = np.array_split(views, num_workers)

        # Convert numpy arrays back to plain lists (json-serializable)
        view_chunks = [list(chunk) for chunk in view_chunks]
        chunk_infos = []
        
        # Calculate optimal threads per worker
        threads_per_worker = _get_optimal_threads(num_workers)

        with mp.Pool(processes=num_workers) as pool:
            jobs = []
            for idx, chunk in enumerate(view_chunks):
                chunk_output_folder = os.path.join(output_folder, f"chunk_{idx}")
                chunk_infos.append((chunk_output_folder, chunk))
                
                # Assign GPU ID round-robin if GPUs are available
                assigned_gpu = None
                if num_gpus > 0:
                    assigned_gpu = idx % num_gpus
                
                jobs.append(
                    pool.apply_async(
                        _render_views_chunk,
                        (file_path, chunk_output_folder, chunk, blender_render_engine, assigned_gpu, threads_per_worker),
                    )
                )
            for j in jobs:
                j.get()

        _merge_blender_chunks(output_folder, chunk_infos, file_path, blender_render_engine)

    if os.path.exists(os.path.join(output_folder, 'transforms.json')):
        # Return list of rendered image paths
        out_renderviews = sorted(
            [
                os.path.join(output_folder, f)
                for f in os.listdir(output_folder)
                if f.lower().endswith((".png", ".jpg", ".jpeg"))
            ]
        )
        return out_renderviews if out_renderviews else None
    return None