# based on https://github.com/DIYer22/bpycv/blob/c576e01622d87eb3534f73bf1a5686bd2463de97/example/ycb_demo.py import bpy import bpycv import os import glob import random example_data_dir = os.environ['BPY_EXAMPLE_DATA'] models = sorted(glob.glob(os.path.join(example_data_dir, "model", "*", "*.obj"))) cat_id_to_model_path = dict(enumerate(sorted(models), 1)) distractors = sorted(glob.glob(os.path.join(example_data_dir, "distractor", "*.obj"))) bpycv.clear_all() bpy.context.scene.frame_set(1) bpy.context.scene.render.engine = "CYCLES" bpy.context.scene.cycles.samples = 32 bpy.context.scene.render.resolution_y = 1024 bpy.context.scene.render.resolution_x = 1024 # A transparency stage for holding rigid body stage = bpycv.add_stage(transparency=True) bpycv.set_cam_pose(cam_radius=1, cam_deg=45) hdri_dir = os.path.join(example_data_dir, "background_and_light") hdri_manager = bpycv.HdriManager( hdri_dir=hdri_dir, download=False ) # if download is True, will auto download .hdr file from HDRI Haven hdri_path = hdri_manager.sample() bpycv.load_hdri_world(hdri_path, random_rotate_z=True) # load 5 objects for index in range(5): cat_id = random.choice(list(cat_id_to_model_path)) model_path = cat_id_to_model_path[cat_id] obj = bpycv.load_obj(model_path) obj.location = ( random.uniform(-0.2, 0.2), random.uniform(-0.2, 0.2), random.uniform(0.1, 0.3), ) obj.rotation_euler = [random.uniform(-3.1415, 3.1415) for _ in range(3)] # set each instance a unique inst_id, which is used to generate instance annotation. obj["inst_id"] = cat_id * 1000 + index with bpycv.activate_obj(obj): bpy.ops.rigidbody.object_add() # load 6 distractors for index in range(6): distractor_path = random.choice(distractors) target_size = random.uniform(0.1, 0.3) distractor = bpycv.load_distractor(distractor_path, target_size=target_size) distractor.location = ( random.uniform(-0.2, 0.2), random.uniform(-0.2, 0.2), random.uniform(0.1, 0.3), ) distractor.rotation_euler = [random.uniform(-3.1415, 3.1415) for _ in range(3)] with bpycv.activate_obj(distractor): bpy.ops.rigidbody.object_add() # run pyhsic engine for 20 frames for i in range(20): bpy.context.scene.frame_set(bpy.context.scene.frame_current + 1) # render image, instance annoatation and depth in one line code result = bpycv.render_data() dataset_dir = "./dataset" result.save(dataset_dir=dataset_dir, fname="0", save_blend=True) print(f'Save to "{dataset_dir}"') print(f'Open "{dataset_dir}/vis/" to see visualize result.')