Crie dados sintéticos para pipelines de visão computacional na AWS

mkdir nugget_images
ffmpeg -i VIDEO.mov ffmpeg nugget_images/nugget_%06d.jpg

class Object3D:
	'''
	object container to store mesh information about the
	given object

	Returns
	the Object3D object
	'''
	def __init__(self, object: Union[bpy.types.Object, str]):
		"""Creates a Object3D object.

		Args:
		obj (Union[bpy.types.Object, str]): Scene object (or it's name)
		"""
		self.object = object
		self.obj_poly = None
		self.mat = None
		self.vert = None
		self.poly = None
		self.bvht = None
		self.calc_mat()
		self.calc_world_vert()
		self.calc_poly()
		self.calc_bvht()

	def calc_mat(self) -> None:
		"""store an instance of the object's matrix_world"""
		self.mat = self.object.matrix_world

	def calc_world_vert(self) -> None:
		"""calculate the verticies from object's matrix_world perspective"""
		self.vert = [self.mat @ v.co for v in self.object.data.vertices]
		self.obj_poly = np.array(self.vert)

	def calc_poly(self) -> None:
		"""store an instance of the object's polygons"""
		self.poly = [p.vertices for p in self.object.data.polygons]

	def calc_bvht(self) -> None:
		"""create a BVHTree from the object's polygon"""
		self.bvht = BVHTree.FromPolygons( self.vert, self.poly )

	def regenerate(self) -> None:
		"""reinstantiate the object's variables;
		used when the object is manipulated after it's creation"""
		self.calc_mat()
		self.calc_world_vert()
		self.calc_poly()
		self.calc_bvht()

	def __repr__(self):
		return "Object3D: " + self.object.__repr__()

class DensityController:
    """Container that controlls the spacial relationship between 3D objects

    Returns:
        DensityController: The DensityController object.
    """
    def __init__(self):
        self.bvhtrees = None
        self.overlaps = None
        self.occupied = None
        self.unoccupied = None
        self.objects3d = []

    def auto_generate_kdtree_cubes(
        self,
        num_objects: int = 100, # max size of nuggets
    ) -> None:
        """
        function to generate physical kdtree cubes given a plane of -resize- size
        this allows us to access each cube's overlap/occupancy status at any given
        time
        
        creates a KDTree collection, a cube, a set of individual cubes, and the 
        BVHTree object for each individual cube

        Args:
            resize (Tuple[float]): the size of a cube to create XYZ.
            cuts (int): how many cuts are made to the cube face
                12 cuts == 13 Rows x 13 Columns  
        """

        # read the nugget,
        # see how large the cube needs to be to encompass a single nugget
        # then touch a parameter to allow it to be smaller or larger (eg more touching)
        bpy.context.view_layer.objects.active = bpy.context.scene.objects.get('nugget_base')
        bpy.ops.object.origin_set(type='ORIGIN_GEOMETRY', center='BOUNDS')
        #create a cube for the bounding box
        bpy.ops.mesh.primitive_cube_add(location=Vector((0,0,0))) 
        #our new cube is now the active object, so we can keep track of it in a variable:
        bound_box = bpy.context.active_object
        bound_box.name = 'CUBE1'
        bpy.context.view_layer.update()
        #copy transforms
        nug_dims = bpy.data.objects["nugget_base"].dimensions
        bpy.data.objects["CUBE1"].dimensions = nug_dims
        bpy.context.view_layer.update()
        bpy.data.objects["CUBE1"].location = bpy.data.objects["nugget_base"].location
        bpy.context.view_layer.update()
        bpy.data.objects["CUBE1"].rotation_euler = bpy.data.objects["nugget_base"].rotation_euler
        bpy.context.view_layer.update()
        print("bound_box.dimensions: ", bound_box.dimensions)
        print("bound_box.location:", bound_box.location)

        # this cube created isn't always square, but we're going to make it square
        # to fit into our 
        x, y, z = bound_box.dimensions
        v = max(x, y)
        if np.round(v) < v:
            v = np.round(v)+1
        bb_x, bb_y = v, v
        bound_box.dimensions = Vector((v, v, z))
        bpy.context.view_layer.update()
        print("bound_box.dimensions updated: ", bound_box.dimensions)
        # now we generate a plane
        # calc the size of the plane given a max number of boxes.

        x, y, z = bound_box.dimensions
        bb_loc = bound_box.location
        bb_rot_eu = bound_box.rotation_euler
        min_area = (x*y)*num_objects
        min_length = min_area / num_objects
        print(min_length)
        # now we generate a plane
        # calc the size of the plane given a max number of boxes.
        bpy.ops.mesh.primitive_plane_add(location=Vector((0,0,0)), size = min_length)
        plane = bpy.context.selected_objects[0]
        plane.name = 'PLANE'
        # move our plane to our background collection
        # current_collection = plane.users_collection
        link_object('PLANE', 'BACKGROUND')
        bpy.context.view_layer.update()

        # New Collection
        my_coll = bpy.data.collections.new("KDTREE")
        # Add collection to scene collection
        bpy.context.scene.collection.children.link(my_coll)
        # now we generate cubes based on the size of the plane.
        bpy.ops.mesh.primitive_cube_add(location=Vector((0,0,0)), size = min_length)
        bpy.context.view_layer.update()
        cube = bpy.context.selected_objects[0]
        cube_dimensions = cube.dimensions
        bpy.context.view_layer.update()
        cube.dimensions = Vector((cube_dimensions[0], cube_dimensions[1], z))
        bpy.context.view_layer.update()
        cube.location = bb_loc
        bpy.context.view_layer.update()
        cube.rotation_euler = bb_rot_eu
        bpy.context.view_layer.update()
        cube.name = 'cube'
        bpy.context.view_layer.update()
        current_collection = cube.users_collection
        link_object('cube', 'KDTREE')
        bpy.context.view_layer.update()

        # get the bb volume and make the proper cuts to the object 
        bb_vol = x*y*z
        cube_vol = cube_dimensions[0]*cube_dimensions[1]*cube_dimensions[2]
        n_cubes = cube_vol / bb_vol
        cuts = n_cubes / ((x+y) / 2)
        cuts = int(np.round(cuts)) - 1 # 
        # select the cube
        for object in bpy.data.objects:
            object.select_set(False)
        bpy.context.view_layer.update()
        for object in bpy.data.objects:
            object.select_set(False)
        bpy.data.objects['cube'].select_set(True) # Blender 2.8x
        bpy.context.view_layer.objects.active = bpy.context.scene.objects.get('cube')
        # set to edit mode
        bpy.ops.object.mode_set(mode='EDIT', toggle=False)
        print('edit mode success')
        # get face_data
        context = bpy.context
        obj = context.edit_object
        me = obj.data
        mat = obj.matrix_world
        bm = bmesh.from_edit_mesh(me)
        up_face = None
        # select upwards facing cube-face
        # https://blender.stackexchange.com/questions/43067/get-a-face-selected-pointing-upwards
        for face in bm.faces:
            if (face.normal-UP_VECTOR).length < EPSILON:
                up_face = face
                break
        assert(up_face)
        # subdivide the edges to get the perfect kdtree cubes
        bmesh.ops.subdivide_edges(bm,
                edges=up_face.edges,
                use_grid_fill=True,
                cuts=cuts)
        bpy.context.view_layer.update()
        # get the center point of each face

        face_data = {}
        sizes = []
        for f, face in enumerate(bm.faces): 
            face_data[f] = {}
            face_data[f]['calc_center_bounds'] = face.calc_center_bounds()
            loc = mat @ face_data[f]['calc_center_bounds']
            face_data[f]['loc'] = loc
            sizes.append(loc[-1])
        # get the most common cube-z; we use this to determine the correct loc
        counter = Counter()
        counter.update(sizes)
        most_common = counter.most_common()[0][0]
        cube_loc = mat @ cube.location
        # get out of edit mode
        bpy.ops.object.mode_set(mode='OBJECT', toggle=False)
        # go to new colection
        bvhtrees = {}
        for f in face_data:
            loc = face_data[f]['loc']
            loc = mat @ face_data[f]['calc_center_bounds']
            print(loc)
            if loc[-1] == most_common:
                # set it back down to the floor because the face is elevated to the
                # top surface of the cube
                loc[-1] = cube_loc[-1]
                bpy.ops.mesh.primitive_cube_add(location=loc, size = x)
                cube = bpy.context.selected_objects[0]
                cube.dimensions = Vector((x, y, z))
                # bpy.context.view_layer.update()
                cube.name = "cube_{}".format(f)
                #my_coll.objects.link(cube)
                link_object("cube_{}".format(f), 'KDTREE')
                #bpy.context.view_layer.update()
                bvhtrees[f] = {
                    'occupied' : 0,
                    'object' : Object3D(cube)
                }
        for object in bpy.data.objects:
            object.select_set(False)
        bpy.data.objects['CUBE1'].select_set(True) # Blender 2.8x
        bpy.ops.object.delete()
        return bvhtrees

    def find_occupied_space(
        self, 
        objects3d: List[Object3D],
    ) -> None:
        """
        discover which cube's bvhtree is occupied in our kdtree space

        Args:
            list of Object3D objects

        """
        count = 0
        occupied = []
        for i in self.bvhtrees:
            bvhtree = self.bvhtrees[i]['object']
            for object3d in objects3d:
                if object3d.bvht.overlap(bvhtree.bvht):
                    self.bvhtrees[i]['occupied'] = 1

    def find_overlapping_objects(
        self, 
        objects3d: List[Object3D],
    ) -> List[Tuple[int]]:
        """
        returns which Object3D objects are overlapping

        Args:
            list of Object3D objects
        
        Returns:
            List of indicies from objects3d that are overlap
        """
        count = 0
        overlaps = []
        for i, x_object3d in enumerate(objects3d):
            for ii, y_object3d in enumerate(objects3d[i+1:]):
                if x_object3d.bvht.overlap(y_object3d.bvht):
                    overlaps.append((i, ii))
        return overlaps

    def calc_most_overlapped(
        self,
        overlaps: List[Tuple[int]]
    ) -> List[Tuple[int]]:
        """
        Algorithm to count the number of edges each index has
        and return a sorted list from most->least with the number
        of edges each index has. 

        Args:
            list of indicies that are overlapping
        
        Returns:
            list of indicies with the total number of overlapps they have 
            [index, count]
        """
        keys = {}
        for x,y in overlaps:
            if x not in keys:
                keys[x] = 0
            if y not in keys:
                keys[y] = 0
            keys[x]+=1
            keys[y]+=1
        # sort by most edges first
        index_counts = sorted(keys.items(), key=lambda x: x[1])[::-1]
        return index_counts
    
    def get_random_unoccupied(
        self
    ) -> Union[int,None]:
        """
        returns a randomly chosen unoccuped kdtree cube

        Return
            either the kdtree cube's key or None (meaning all spaces are
            currently occupied)
            Union[int,None]
        """
        unoccupied = []
        for i in self.bvhtrees:
            if not self.bvhtrees[i]['occupied']:
                unoccupied.append(i)
        if unoccupied:
            random.shuffle(unoccupied)
            return unoccupied[0]
        else:
            return None

    def regenerate(
        self,
        iterable: Union[None, List[Object3D]] = None
    ) -> None:
        """
        this function recalculates each objects world-view information
        we default to None, which means we're recalculating the self.bvhtree cubes

        Args:
            iterable (None or List of Object3D objects). if None, we default to
            recalculating the kdtree
        """
        if isinstance(iterable, list):
            for object in iterable:
                object.regenerate()
        else:
            for idx in self.bvhtrees:
                self.bvhtrees[idx]['object'].regenerate()
                self.update_tree(idx, occupied=0)       

    def process_trees_and_objects(
        self,
        objects3d: List[Object3D],
    ) -> List[Tuple[int]]:
        """
        This function finds all overlapping objects within objects3d,
        calculates the objects with the most overlaps, searches within
        the kdtree cube space to see which cubes are occupied. It then returns 
        the edge-counts from the most overlapping objects

        Args:
            list of Object3D objects
        Returns
            this returns the output of most_overlapped
        """
        overlaps = self.find_overlapping_objects(objects3d)
        most_overlapped = self.calc_most_overlapped(overlaps)
        self.find_occupied_space(objects3d)
        return most_overlapped

    def move_objects(
        self, 
        objects3d: List[Object3D],
        most_overlapped: List[Tuple[int]],
        z_increase_offset: float = 2.,
    ) -> None:
        """
        This function iterates through most-overlapped, and uses 
        the index to extract the matching object from object3d - it then
        finds a random unoccupied kdtree cube and moves the given overlapping
        object to that space. It does this for each index from the most-overlapped
        function

        Args:
            objects3d: list of Object3D objects
            most_overlapped: a list of tuples (index, count) - where index relates to
                where it's found in objects3d and count - how many times it overlaps 
                with other objects
            z_increase_offset: this value increases the Z value of the object in order to
                make it appear as though it's off the floor. If you don't augment this value
                the object looks like it's 'inside' the ground plane
        """
        for idx, cnt in most_overlapped:
            object3d = objects3d[idx]
            unoccupied_idx = self.get_random_unoccupied()
            if unoccupied_idx:
                object3d.object.location =  self.bvhtrees[unoccupied_idx]['object'].object.location
                # ensure the nuggest is above the groundplane
                object3d.object.location[-1] = z_increase_offset
                self.update_tree(unoccupied_idx, occupied=1)
    
    def dynamic_movement(
        self, 
        objects3d: List[Object3D],
        tries: int = 100,
        z_offset: float = 2.,
    ) -> None:
        """
        This function resets all objects to get their current positioning
        and randomly moves objects around in an attempt to avoid any object
        overlaps (we don't want two objects to be spawned in the same position)

        Args:
            objects3d: list of Object3D objects
            tries: int the number of times we want to move objects to random spaces
                to ensure no overlaps are present.
            z_offset: this value increases the Z value of the object in order to
                make it appear as though it's off the floor. If you don't augment this value
                the object looks like it's 'inside' the ground plane (see `move_objects`)
        """
    
        # reset all objects
        self.regenerate(objects3d)
        # regenerate bvhtrees
        self.regenerate(None)

        most_overlapped = self.process_trees_and_objects(objects3d)
        attempts = 0
        while most_overlapped:
            if attempts>=tries:
                break
            self.move_objects(objects3d, most_overlapped, z_offset)
            attempts+=1
            # recalc objects
            self.regenerate(objects3d)
            # regenerate bvhtrees
            self.regenerate(None)
            # recalculate overlaps
            most_overlapped = self.process_trees_and_objects(objects3d)

    def generate_spawn_point(
        self,
    ) -> Vector:
        """
        this function generates a random spawn point by finding which
        of the kdtree-cubes are unoccupied, and returns one of those

        Returns
            the Vector location of the kdtree-cube that's unoccupied
        """
        idx = self.get_random_unoccupied()
        print(idx)
        self.update_tree(idx, occupied=1)
        return self.bvhtrees[idx]['object'].object.location

    def update_tree(
        self,
        idx: int,
        occupied: int,
    ) -> None:
        """
        this function updates the given state (occupied vs. unoccupied) of the
        kdtree given the idx

        Args:
            idx: int
            occupied: int
        """
        self.bvhtrees[idx]['occupied'] = occupied

@gin.configurable("run")
@zpy.blender.save_and_revert
def run(
    max_num_nuggets: int = 100,
    jitter_mesh: bool = True,
    jitter_nugget_scale: bool = True,
    jitter_material: bool = True,
    jitter_nugget_material: bool = False,
    number_of_random_materials: int = 50,
    nugget_texture_path: str = os.getcwd()+"/nugget_textures",
    annotations_path = os.getcwd()+'/nugget_data',
):
    """
    Main run function.
    """
    density_controller = DensityController()
    # Random seed results in unique behavior
    zpy.blender.set_seed(random.randint(0,1000000000))

    # Create the saver object
    saver = zpy.saver_image.ImageSaver(
        description="Image of the randomized Amazon nuggets",
        output_dir=annotations_path,
    )
    saver.add_category(name="nugget")

    # Make a list of source nugget objects
    source_nugget_objects = []
    for obj in zpy.objects.for_obj_in_collections(
        [
            bpy.data.collections["NUGGET"],
        ]
    ):
        assert(obj!=None)

        # pass on everything not named nugget
        if 'nugget_base' not in obj.name:
            print('passing on {}'.format(obj.name))
            continue
        zpy.objects.segment(obj, name="nugget", as_category=True) #color=nugget_seg_color
        print("zpy.objects.segment: check {}".format(obj.name))
        source_nugget_objects.append(obj.name)

    # move nugget point up 10 z's so it won't collide with base-cube
    bpy.data.objects["nugget_base"].location[-1] = 10

    # Save the position of the camera and light
    # create light and camera
    zpy.objects.save_pose("Camera")
    zpy.objects.save_pose("Sun")
    zpy.objects.save_pose("Plane")
    zpy.objects.save_pose("Main Axis")
    axis = bpy.data.objects['Main Axis']
    print('saving poses')
    # add some parameters to this 

    # get the plane-3d object
    plane3d = Object3D(bpy.data.objects['Plane'])

    # generate kdtree cubes
    density_controller.generate_kdtree_cubes()

    # Pre-create a bunch of random textures
    #random_materials = [
    #    zpy.material.random_texture_mat() for _ in range(number_of_random_materials)
    #]
    p = os.path.abspath(os.getcwd()+'/random_textures')
    print(p)
    random_materials = []
    for x in os.listdir(p):
        texture_path = Path(os.path.join(p,x))
        y = zpy.material.make_mat_from_texture(texture_path, name=texture_path.stem)
        random_materials.append(y)
    #print(random_materials[0])

    # Pre-create a bunch of random textures
    random_nugget_materials = [
        random_nugget_texture_mat(Path(nugget_texture_path)) for _ in range(number_of_random_materials)
    ]

    # Run the sim.
    for step_idx in zpy.blender.step():
        density_controller.generate_kdtree_cubes()

        objects3d = []
        num_nuggets = random.randint(40, max_num_nuggets)
        log.info(f"Spawning {num_nuggets} nuggets.")
        spawned_nugget_objects = []
        for _ in range(num_nuggets):

            # Choose location to spawn nuggets
            spawn_point = density_controller.generate_spawn_point()
            # manually spawn above the floor
            # spawn_point[-1] = 1.8 #2.0

            # Pick a random object to spawn
            _name = random.choice(source_nugget_objects)
            log.info(f"Spawning a copy of source nugget {_name} at {spawn_point}")
            obj = zpy.objects.copy(
                bpy.data.objects[_name],
                collection=bpy.data.collections["SPAWNED"],
                is_copy=True,
            )

            obj.location = spawn_point
            obj.matrix_world = mathutils.Matrix.Translation(spawn_point)
            spawned_nugget_objects.append(obj)

            # Segment the newly spawned nugget as an instance
            zpy.objects.segment(obj)

            # Jitter final pose of the nugget a little
            zpy.objects.jitter(
                obj,
                rotate_range=(
                    (0.0, 0.0),
                    (0.0, 0.0),
                    (-math.pi * 2, math.pi * 2),
                ),
            )

            if jitter_nugget_scale:
                # Jitter the scale of each nugget
                zpy.objects.jitter(
                    obj,
                    scale_range=(
                        (0.8, 2.0), #1.2
                        (0.8, 2.0), #1.2
                        (0.8, 2.0), #1.2
                    ),
                )

            if jitter_mesh:
                # Jitter (deform) the mesh of each nugget
                zpy.objects.jitter_mesh(
                    obj=obj,
                    scale=(
                        random.uniform(0.01, 0.03),
                        random.uniform(0.01, 0.03),
                        random.uniform(0.01, 0.03),
                    ),
                )

            if jitter_nugget_material:
                # Jitter the material (apperance) of each nugget
                for i in range(len(obj.material_slots)):
                    obj.material_slots[i].material = random.choice(random_nugget_materials)
                    zpy.material.jitter(obj.material_slots[i].material)          

            # create 3d obj for movement
            nugget3d = Object3D(obj)

            # make sure the bottom most part of the nugget is NOT
            # inside the plane-object       
            plane_overlap(plane3d, nugget3d)

            objects3d.append(nugget3d)

        # ensure objects aren't on top of each other
        density_controller.dynamic_movement(objects3d)

        # Return camera to original position
        zpy.objects.restore_pose("Camera")
        zpy.objects.restore_pose("Main Axis")
        zpy.objects.restore_pose("Camera")
        zpy.objects.restore_pose("Main Axis")

        # assert these are the correct versions...
        assert(bpy.data.objects["Camera"].location == Vector((0,0,100)))
        assert(bpy.data.objects["Main Axis"].location == Vector((0,0,0)))
        assert(bpy.data.objects["Main Axis"].rotation_euler == Euler((0,0,0)))

        # alter the Z ditance with the camera
        bpy.data.objects["Camera"].location = (0, 0, random.uniform(0.75, 3.5)*100)

        # alter the main-axis beta/gamma params
        top_down_mostly = False 
        if top_down_mostly:
            zpy.objects.rotate(
                bpy.data.objects["Main Axis"],
                rotation=(
                    random.uniform(0.05, 0.05),
                    random.uniform(0.05, 0.05),
                    random.uniform(0.05, 0.05),
                ),
            )
        else:
            zpy.objects.rotate(
                bpy.data.objects["Main Axis"],
                rotation=(
                    random.uniform(-1., 1.),
                    random.uniform(-1., 1.),
                    random.uniform(-1., 1.),
                ),
            )

        print(bpy.data.objects["Main Axis"].rotation_euler)
        print(bpy.data.objects["Camera"].location)

        # change the background material
        # Randomize texture of shelf, floors and walls
        for obj in bpy.data.collections["BACKGROUND"].all_objects:
            for i in range(len(obj.material_slots)):
                # TODO
                # Pick one of the random materials
                obj.material_slots[i].material = random.choice(random_materials)
                if jitter_material:
                    zpy.material.jitter(obj.material_slots[i].material)
                # Sets the material relative to the object
                obj.material_slots[i].link = "OBJECT"
        # Pick a random hdri (from the local textures folder for background background)
        zpy.hdris.random_hdri()
        # Return light to original position
        zpy.objects.restore_pose("Sun")

        # Jitter the light position
        zpy.objects.jitter(
            "Sun",
            translate_range=(
                (-5, 5),
                (-5, 5),
                (-5, 5),
            ),
        )
        bpy.data.objects["Sun"].data.energy = random.uniform(0.5, 7)

# we hide the cube objects
for obj in         # we hide the cube objects
        for obj in bpy.data.objects:
            if 'cube' in obj.name:
                obj.hide_render = True
                try:
                    zpy.objects.toggle_hidden(obj, hidden=True)
                except:
                    # deal with this exception here...
                    pass
        # we hide our base nugget object
        bpy.data.objects["nugget_base"].hide_render = True
        zpy.objects.toggle_hidden(bpy.data.objects["nugget_base"], hidden=True)

        # create the image name
        image_uuid = str(uuid.uuid4())

        # Name for each of the output images
        rgb_image_name = format_image_string(image_uuid, 'rgb')
        iseg_image_name = format_image_string(image_uuid, 'iseg')
        depth_image_name = format_image_string(image_uuid, 'depth')

        zpy.render.render(
            rgb_path=saver.output_dir / rgb_image_name,
            iseg_path=saver.output_dir / iseg_image_name,
            depth_path=saver.output_dir / depth_image_name,
        )

        # Add images to saver
        saver.add_image(
            name=rgb_image_name,
            style="default",
            output_path=saver.output_dir / rgb_image_name,
            frame=step_idx,
        )
    
        saver.add_image(
            name=iseg_image_name,
            style="segmentation",
            output_path=saver.output_dir / iseg_image_name,
            frame=step_idx,
        )
        saver.add_image(
            name=depth_image_name,
            style="depth",
            output_path=saver.output_dir / depth_image_name,
            frame=step_idx,
        )

        # ideally in this thread, we'll open the anno file
        # and write to it directly, saving it after each generation
        for obj in spawned_nugget_objects:
            # Add annotation to segmentation image
            saver.add_annotation(
                image=rgb_image_name,
                category="nugget",
                seg_image=iseg_image_name,
                seg_color=tuple(obj.seg.instance_color),
            )

        # Delete the spawned nuggets
        zpy.objects.empty_collection(bpy.data.collections["SPAWNED"])

        # Write out annotations
        saver.output_annotated_images()
        saver.output_meta_analysis()

        # # ZUMO Annotations
        _output_zumo = _OutputZUMO(saver=saver, annotation_filename = Path(image_uuid + ".zumo.json"))
        _output_zumo.output_annotations()
        # change the name here..
        saver.output_annotated_images()
        saver.output_meta_analysis()

        # remove the memory of the annotation to free RAM
        saver.annotations = []
        saver.images = {}
        saver.image_name_to_id = {}
        saver.seg_annotations_color_to_id = {}

    log.info("Simulation complete.")

if __name__ == "__main__":

    # Set the logger levels
    zpy.logging.set_log_levels("info")

    # Parse the gin-config text block
    # hack to read a specific gin config
    parse_config_from_file('nugget_config.gin')

    # Run the sim
    run()

tar cvf working_blender_dir.tar.gz working_blender_dir
scp -i "your.pem" working_blender_dir.tar.gz ubuntu@EC2-INSTANCE.compute.amazonaws.com:/home/ubuntu/working_blender_dir.tar.gz

tar xvf working_blender_dir.tar.gz

blender working_blender_dir/nugget.blend --background --python working_blender_dir/create_synthetic_nuggets.py

{
    "metadata": {
        "description": "3D data of a nugget!",
        "contributor": "Matt Krzus",
        "url": "krzum@amazon.com",
        "year": "2021",
        "date_created": "20210924_000000",
        "save_path": "/home/ubuntu/working_blender_dir/nugget_data"
    },
    "categories": {
        "0": {
            "name": "nugget",
            "supercategories": [],
            "subcategories": [],
            "color": [
                0.0,
                0.0,
                0.0
            ],
            "count": 6700,
            "subcategory_count": [],
            "id": 0
        }
    },
    "images": {
        "0": {
            "name": "a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.rgb.png",
            "style": "default",
            "output_path": "/home/ubuntu/working_blender_dir/nugget_data/a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.rgb.png",
            "relative_path": "a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.rgb.png",
            "frame": 97,
            "width": 640,
            "height": 480,
            "id": 0
        },
        "1": {
            "name": "a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.iseg.png",
            "style": "segmentation",
            "output_path": "/home/ubuntu/working_blender_dir/nugget_data/a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.iseg.png",
            "relative_path": "a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.iseg.png",
            "frame": 97,
            "width": 640,
            "height": 480,
            "id": 1
        },
        "2": {
            "name": "a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.depth.png",
            "style": "depth",
            "output_path": "/home/ubuntu/working_blender_dir/nugget_data/a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.depth.png",
            "relative_path": "a0bb1fd3-c2ec-403c-aacf-07e0c07f4fdd.depth.png",
            "frame": 97,
            "width": 640,
            "height": 480,
            "id": 2
        }
    },
    "annotations": [
        {
            "image_id": 0,
            "category_id": 0,
            "id": 0,
            "seg_color": [
                1.0,
                0.6000000238418579,
                0.9333333373069763
            ],
            "color": [
                1.0,
                0.6,
                0.9333333333333333
            ],
            "segmentation": [
                [
                    299.0,
                    308.99,
                    292.0,
                    308.99,
                    283.01,
                    301.0,
                    286.01,
                    297.0,
                    285.01,
                    294.0,
                    288.01,
                    285.0,
                    283.01,
                    275.0,
                    287.0,
                    271.01,
                    294.0,
                    271.01,
                    302.99,
                    280.0,
                    305.99,
                    286.0,
                    305.99,
                    303.0,
                    302.0,
                    307.99,
                    299.0,
                    308.99
                ]
            ],
            "bbox": [
                283.01,
                271.01,
                22.980000000000018,
                37.98000000000002
            ],
            "area": 667.0802000000008,
            "bboxes": [
                [
                    283.01,
                    271.01,
                    22.980000000000018,
                    37.98000000000002
                ]
            ],
            "areas": [
                667.0802000000008
            ]
        },
        {
            "image_id": 0,
            "category_id": 0,
            "id": 1,
            "seg_color": [
                1.0,
                0.4000000059604645,
                1.0
            ],
            "color": [
                1.0,
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            ],
            "segmentation": [
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            ],
            "bbox": [
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            "area": 743.5502000000008,
            "bboxes": [
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            ],
            "areas": [
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        },
...
...
...