feat: add batch 3D generation script with VRAM optimization
- Add batch_generate.py: two-phase pipeline (shape→texture) that loads models sequentially to avoid OOM on RTX 3080 - Fix mesh_utils.py: make bpy import lazy so load_mesh/save_mesh work without Blender installed - Phase 1: shape generation for all images, then unload - Phase 2: texture generation for all meshes, then unload - Skip already-generated outputs for resumability - Tested: 9/9 images successfully generated textured GLB models Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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Akasei
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batch_generate.py
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257
batch_generate.py
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"""
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Batch 3D model generation script for Hunyuan3D-2.1.
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Optimized for RTX 3080 (20GB VRAM) by sequential model loading:
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Phase 1: Load shape model → generate all meshes → unload
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Phase 2: Load texture model → texture all meshes → unload
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"""
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import sys
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sys.path.insert(0, './hy3dshape')
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sys.path.insert(0, './hy3dpaint')
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try:
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from torchvision_fix import apply_fix
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apply_fix()
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except Exception as e:
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print(f"Warning: torchvision fix: {e}")
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import os
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import gc
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import time
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import glob
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import torch
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import trimesh
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import numpy as np
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from PIL import Image
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from pathlib import Path
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INPUT_DIR = "test/images"
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OUTPUT_DIR = "test/models"
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MODEL_PATH = "tencent/Hunyuan3D-2.1"
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SUBFOLDER = "hunyuan3d-dit-v2-1"
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SHAPE_STEPS = 50
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GUIDANCE_SCALE = 7.5
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SEED = 1234
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OCTREE_RESOLUTION = 256
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NUM_CHUNKS = 200000
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TEXGEN_MAX_VIEWS = 6
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TEXGEN_RESOLUTION = 512
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def clear_gpu():
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"""Aggressively free GPU memory."""
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gc.collect()
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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torch.cuda.synchronize()
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def get_image_files(input_dir):
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"""Get all supported image files from input directory."""
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extensions = ['*.jpg', '*.jpeg', '*.png', '*.bmp', '*.webp']
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files = []
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for ext in extensions:
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files.extend(glob.glob(os.path.join(input_dir, ext)))
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files.extend(glob.glob(os.path.join(input_dir, ext.upper())))
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return sorted(set(files))
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def phase1_shape_generation(image_files, output_dir):
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"""Phase 1: Load shape model, generate all meshes, unload."""
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print("\n" + "=" * 60)
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print("PHASE 1: Shape Generation")
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print("=" * 60)
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from hy3dshape.rembg import BackgroundRemover
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from hy3dshape.pipelines import Hunyuan3DDiTFlowMatchingPipeline
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from hy3dshape.pipelines import export_to_trimesh
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from hy3dshape import FaceReducer
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print("Loading shape model...")
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t0 = time.time()
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rmbg = BackgroundRemover()
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pipeline = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained(
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MODEL_PATH, subfolder=SUBFOLDER, use_safetensors=False, device='cuda'
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)
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face_reducer = FaceReducer()
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print(f"Shape model loaded in {time.time()-t0:.1f}s")
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print(f"GPU memory: {torch.cuda.memory_allocated()/1024**3:.2f} GB")
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results = {}
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for i, img_path in enumerate(image_files):
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name = Path(img_path).stem
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item_dir = os.path.join(output_dir, name)
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os.makedirs(item_dir, exist_ok=True)
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mesh_path = os.path.join(item_dir, "white_mesh.obj")
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if os.path.exists(mesh_path):
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print(f"[{i+1}/{len(image_files)}] {name}: shape exists, skipping")
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results[name] = {"image": img_path, "mesh": mesh_path, "dir": item_dir}
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continue
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print(f"\n[{i+1}/{len(image_files)}] Generating shape for: {name}")
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t1 = time.time()
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try:
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image = Image.open(img_path).convert("RGBA")
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if image.mode == "RGB" or image.getchannel("A").getextrema()[0] > 250:
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image = rmbg(image.convert("RGB"))
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generator = torch.Generator().manual_seed(SEED)
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outputs = pipeline(
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image=image,
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num_inference_steps=SHAPE_STEPS,
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guidance_scale=GUIDANCE_SCALE,
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generator=generator,
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octree_resolution=OCTREE_RESOLUTION,
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num_chunks=NUM_CHUNKS,
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output_type='mesh',
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)
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mesh = export_to_trimesh(outputs)[0]
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# Face reduction for texture gen compatibility
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mesh = face_reducer(mesh)
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mesh.export(mesh_path, include_normals=False)
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# Save input image alongside mesh for texture gen
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input_copy = os.path.join(item_dir, "input.png")
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image.save(input_copy)
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results[name] = {"image": img_path, "mesh": mesh_path, "dir": item_dir}
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print(f" Done in {time.time()-t1:.1f}s | faces: {mesh.faces.shape[0]}")
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except Exception as e:
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print(f" ERROR: {e}")
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import traceback; traceback.print_exc()
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results[name] = {"image": img_path, "mesh": None, "dir": item_dir, "error": str(e)}
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clear_gpu()
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# Unload shape model
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print("\nUnloading shape model...")
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del pipeline, rmbg, face_reducer
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clear_gpu()
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print(f"GPU memory after unload: {torch.cuda.memory_allocated()/1024**3:.2f} GB")
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return results
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def phase2_texture_generation(results, output_dir):
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"""Phase 2: Load texture model, texture all meshes, unload."""
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print("\n" + "=" * 60)
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print("PHASE 2: Texture Generation")
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print("=" * 60)
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meshes_to_texture = {k: v for k, v in results.items() if v.get("mesh")}
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if not meshes_to_texture:
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print("No meshes to texture!")
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return results
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from hy3dpaint.textureGenPipeline import Hunyuan3DPaintPipeline, Hunyuan3DPaintConfig
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from hy3dpaint.convert_utils import create_glb_with_pbr_materials
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print("Loading texture model...")
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t0 = time.time()
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conf = Hunyuan3DPaintConfig(TEXGEN_MAX_VIEWS, TEXGEN_RESOLUTION)
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conf.realesrgan_ckpt_path = "hy3dpaint/ckpt/RealESRGAN_x4plus.pth"
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conf.multiview_cfg_path = "hy3dpaint/cfgs/hunyuan-paint-pbr.yaml"
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conf.custom_pipeline = "hy3dpaint/hunyuanpaintpbr"
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tex_pipeline = Hunyuan3DPaintPipeline(conf)
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print(f"Texture model loaded in {time.time()-t0:.1f}s")
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print(f"GPU memory: {torch.cuda.memory_allocated()/1024**3:.2f} GB")
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for i, (name, info) in enumerate(meshes_to_texture.items()):
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item_dir = info["dir"]
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mesh_path = info["mesh"]
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img_path = info["image"]
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textured_obj = os.path.join(item_dir, "textured_mesh.obj")
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textured_glb = os.path.join(item_dir, "textured_mesh.glb")
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if os.path.exists(textured_glb):
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print(f"[{i+1}/{len(meshes_to_texture)}] {name}: textured mesh exists, skipping")
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results[name]["textured_glb"] = textured_glb
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continue
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print(f"\n[{i+1}/{len(meshes_to_texture)}] Texturing: {name}")
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t1 = time.time()
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try:
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output_path = tex_pipeline(
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mesh_path=mesh_path,
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image_path=img_path,
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output_mesh_path=textured_obj,
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save_glb=False,
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)
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# Convert OBJ to GLB with PBR materials
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textures = {
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'albedo': output_path.replace('.obj', '.jpg'),
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'metallic': output_path.replace('.obj', '_metallic.jpg'),
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'roughness': output_path.replace('.obj', '_roughness.jpg'),
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}
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create_glb_with_pbr_materials(output_path, textures, textured_glb)
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results[name]["textured_obj"] = output_path
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results[name]["textured_glb"] = textured_glb
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print(f" Done in {time.time()-t1:.1f}s")
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print(f" Output: {textured_glb}")
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except Exception as e:
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print(f" ERROR: {e}")
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import traceback; traceback.print_exc()
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results[name]["tex_error"] = str(e)
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clear_gpu()
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# Unload texture model
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print("\nUnloading texture model...")
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del tex_pipeline
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clear_gpu()
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print(f"GPU memory after unload: {torch.cuda.memory_allocated()/1024**3:.2f} GB")
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return results
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def main():
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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image_files = get_image_files(INPUT_DIR)
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if not image_files:
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print(f"No images found in {INPUT_DIR}")
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return
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print(f"Found {len(image_files)} images:")
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for f in image_files:
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print(f" - {os.path.basename(f)}")
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total_start = time.time()
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# Phase 1: Shape generation (shape model only in VRAM)
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results = phase1_shape_generation(image_files, OUTPUT_DIR)
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# Phase 2: Texture generation (texture model only in VRAM)
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results = phase2_texture_generation(results, OUTPUT_DIR)
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# Summary
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print("\n" + "=" * 60)
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print("SUMMARY")
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print("=" * 60)
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total_time = time.time() - total_start
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success = sum(1 for v in results.values() if v.get("textured_glb"))
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shape_only = sum(1 for v in results.values() if v.get("mesh") and not v.get("textured_glb"))
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failed = sum(1 for v in results.values() if not v.get("mesh"))
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for name, info in results.items():
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status = "✓ textured" if info.get("textured_glb") else (
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"△ shape only" if info.get("mesh") else "✗ failed"
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)
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print(f" {name}: {status}")
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print(f"\nTotal: {len(results)} | Success: {success} | Shape only: {shape_only} | Failed: {failed}")
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print(f"Total time: {total_time:.1f}s ({total_time/60:.1f}m)")
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print(f"Output directory: {os.path.abspath(OUTPUT_DIR)}")
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if __name__ == "__main__":
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main()
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