"""Render a FLAME mesh overlay with a separately obtained FLAME model's topology.""" import argparse import pickle from pathlib import Path import numpy as np from PIL import Image, ImageDraw from load_sample import load_sample def visualize(sample, faces, output): camera = sample["camera"] vertices = sample["vertices_world"] @ np.asarray(camera["R"]).T + np.asarray(camera["t"]) K = np.asarray(camera["K"]) projection = vertices @ K.T assert (vertices[:, 2] > 0).all() uv = projection[:, :2] / projection[:, 2:] image = Image.fromarray(sample["image"]) width, height = image.size assert [width, height] == [camera["width"], camera["height"]] # Painter's algorithm, back to front; opaque triangles hide rear surfaces. mesh = Image.new("RGB", image.size, (0, 0, 0)) mask = Image.new("L", image.size, 0) draw, draw_mask = ImageDraw.Draw(mesh), ImageDraw.Draw(mask) triangles = vertices[faces] normals = np.cross(triangles[:, 1] - triangles[:, 0], triangles[:, 2] - triangles[:, 0]) normals /= np.maximum(np.linalg.norm(normals, axis=1, keepdims=True), 1e-12) colors = ((normals * 0.5 + 0.5) * 255).astype(np.uint8) for index in np.argsort(triangles[..., 2].mean(axis=1))[::-1]: points = [tuple(p) for p in uv[faces[index]].tolist()] draw.polygon(points, fill=tuple(colors[index].tolist())) draw_mask.polygon(points, fill=255) overlay = Image.composite(Image.blend(image, mesh, 0.55), image, mask) x0, y0, x1, y1 = sample["metadata"]["bbox_xyxy"] ImageDraw.Draw(overlay).rectangle((x0, y0, x1, y1), outline=(255, 180, 0), width=2) segmentation = Image.fromarray(np.repeat((sample["foreground"] * 255).astype(np.uint8)[..., None], 3, axis=2)) result = Image.new("RGB", (width * 3, height)) for index, panel in enumerate((image, overlay, segmentation)): result.paste(panel, (index * width, 0)) result.thumbnail((1500, 900)) result.save(output) if __name__ == "__main__": parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("--root", type=Path, required=True) parser.add_argument("--subject", required=True) parser.add_argument("--frame", required=True) parser.add_argument("--camera", required=True) parser.add_argument("--flame-model", type=Path, required=True) parser.add_argument("--output", type=Path, required=True) args = parser.parse_args() with args.flame_model.open("rb") as stream: faces = np.asarray(pickle.load(stream, encoding="latin1")["f"], dtype=np.int32) visualize(load_sample(args.root, args.subject, args.frame, args.camera), faces, args.output)