From 7e12e27446ce0e92636d42b0381e8b71c07892a3 Mon Sep 17 00:00:00 2001
From: PrachiUkey <prachi.ukey@flamapp.com>
Date: Thu, 24 Jul 2025 17:49:39 +0530
Subject: [PATCH] Create single_channel.py

render and refine through single channel
---
 single_channel.py | 80 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 80 insertions(+)
 create mode 100644 single_channel.py

diff --git a/single_channel.py b/single_channel.py
new file mode 100644
index 0000000..4bf9122
--- /dev/null
+++ b/single_channel.py
@@ -0,0 +1,80 @@
+from core.remesh import calc_vertex_normals
+from core.opt import MeshOptimizer
+from util.func import load_obj, make_sphere, make_star_cameras, normalize_vertices, save_obj
+from util.render import NormalsRenderer
+from tqdm import tqdm
+from util.snapshot import snapshot
+try:
+    from util.view import show
+except:
+    show = None
+
+from pathlib import Path
+import imageio
+import torch
+import time
+
+def save_images_new(images, dir):
+    dir = Path(dir)
+    dir.mkdir(parents=True, exist_ok=True)
+    images = images.detach().cpu()
+
+    for i in range(images.shape[0]):
+        img = (images[i] * 255).clamp(max=255).type(torch.uint8).numpy()
+
+        # Handle grayscale (1 channel) by squeezing
+        if img.ndim == 3 and img.shape[-1] == 1:
+            img = img.squeeze(-1)
+
+        imageio.imwrite(dir / f'{i:02d}.png', img)
+
+
+fname = 'data/lucy.obj'
+steps = 1000
+snapshot_step = 1
+
+# Setup cameras and renderer
+mv, proj = make_star_cameras(4, 2)
+renderer = NormalsRenderer(mv, proj, [512, 512])
+
+# Load and normalize target mesh
+target_vertices, target_faces = load_obj(fname)
+target_vertices = normalize_vertices(target_vertices)
+target_normals = calc_vertex_normals(target_vertices, target_faces)
+
+# Render target depth maps (only depth channel)
+target_depth = renderer.render(target_vertices, target_normals, target_faces)[..., 0]
+save_images_new(target_depth, './out/target_depth/')
+
+# Initialize mesh optimizer with a sphere
+vertices, faces = make_sphere(level=2, radius=.5)
+opt = MeshOptimizer(vertices, faces)
+vertices = opt.vertices
+snapshots = []
+
+# Optimization loop on depth maps only
+for i in tqdm(range(steps)):
+    opt.zero_grad()
+    normals = calc_vertex_normals(vertices, faces)
+    images = renderer.render(vertices, normals, faces)[..., 0]  # keep only depth
+
+    loss = (images - target_depth).abs().mean()
+    
+
+    loss.backward()
+    opt.step()
+
+    if show and i % snapshot_step == 0:
+        snapshots.append(snapshot(opt))
+
+    vertices, faces = opt.remesh()
+
+# Save final optimized mesh with a timestamped name
+timestamp = int(time.time())
+save_obj(vertices, faces, f'./out/result_{timestamp}.obj')
+
+# Save final depth map
+save_images_new(images, './out/final_depth/')
+
+if show:
+    show(target_vertices, target_faces, snapshots)