HDR_Pretrain / instanthdr_render.py
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import bpy
import os
import json
import math
import numpy as np
import random
from math import radians
import struct
import mathutils
# --- Config Parameters ---
CONFIG = {
"RESULTS_PATH": os.environ.get("RESULTS_PATH"),
"EXPOSURES": [0.125, 0.25, 1.0, 2.0, 8.0],
# "EXPOSURES": [0.666, 0.333, 0.166, 0.1, 0.05],
# "EXPOSURES": [0.333, 0.125, 0.066, 0.0333, 0.0166],
# "EXPOSURES": [0.333, 0.166, 0.1, 0.05, 0.0222],
# "EXPOSURES": [2.0, 1.0, 0.5, 0.25, 0.125],
# "EXPOSURES": [0.03125, 0.125, 0.5, 2.0, 8],
# "EXPOSURES": [0.0625, 0.25, 1, 4.0, 16],
# "EXPOSURES": [0.125, 0.5, 2.0, 8.0, 32.0],
# "EXPOSURES": [8, 32, 128, 512, 2048],
# ================ Upload From Camera ================
"ROWS": 5,
"COLS": 7,
"ROT_STEP": 2.5,
# "ROT_STEP": 5.0,
"RESOLUTION": 448,
"SAMPLES": 2048,
"TONEMAP_POOL": ['AgX', 'Filmic', 'Standard'],
}
chosen_tonemap = None
import math
def update_config_from_camera():
cam = bpy.data.objects.get('Camera')
if not cam:
print("Error: No object named 'Camera' found in the scene")
return
loc = cam.location
CONFIG["INIT_LOC"] = np.array([[loc.x], [loc.z], [-loc.y]])
CONFIG["RADIUS"] = loc.length
CONFIG["MAX_DISTANCE"] = loc.length * 1.5
rot = cam.rotation_euler
pitch = math.degrees(rot.x) - 90
yaw = math.degrees(rot.z)
roll = math.degrees(rot.y)
CONFIG["INIT_ROT"] = [pitch, yaw, roll]
print(f"--- CONFIG updated automatically ---")
print(f"INIT_LOC: {CONFIG['INIT_LOC'].flatten()}")
print(f"INIT_ROT: {CONFIG['INIT_ROT']}")
print(f"RADIUS: {CONFIG['RADIUS']:.4f}")
print(f"MAX_DISTANCE: {CONFIG['MAX_DISTANCE']:.4f}")
def setup_environment():
global chosen_tonemap
scene = bpy.context.scene
scene.render.engine = 'CYCLES'
scene.cycles.samples = CONFIG["SAMPLES"]
scene.render.resolution_x = CONFIG["RESOLUTION"]
scene.render.resolution_y = CONFIG["RESOLUTION"]
scene.render.resolution_percentage = 100
scene.render.dither_intensity = 0.0
scene.render.film_transparent = True
scene.render.use_persistent_data = True
# Default HDR output settings
scene.render.image_settings.file_format = 'OPEN_EXR'
scene.render.image_settings.color_depth = '32'
# Randomly select Tonemapping
chosen_tonemap = random.choice(CONFIG["TONEMAP_POOL"]) if chosen_tonemap is None else chosen_tonemap
bpy.context.scene.view_settings.view_transform = chosen_tonemap
# GPU acceleration
try:
cprefs = bpy.context.preferences.addons['cycles'].preferences
cprefs.compute_device_type = 'OPTIX'
cprefs.get_devices()
for d in cprefs.devices: d.use = True
scene.cycles.device = 'GPU'
except:
print("Using CPU Rendering...")
def setup_nodes(save_root):
scene = bpy.context.scene
scene.use_nodes = True
tree = scene.node_tree
tree.nodes.clear()
rl = tree.nodes.new('CompositorNodeRLayers')
scene.view_layers["ViewLayer"].use_pass_normal = True
scene.view_layers["ViewLayer"].use_pass_z = True
# --- 1. Depth and normal output (PNG) ---
aux_out = tree.nodes.new('CompositorNodeOutputFile')
aux_out.format.file_format = 'PNG'
map_node = tree.nodes.new('CompositorNodeMapRange')
map_node.inputs['From Max'].default_value = CONFIG["MAX_DISTANCE"]
map_node.inputs['To Min'].default_value = 1
map_node.inputs['To Max'].default_value = 0
tree.links.new(rl.outputs['Depth'], map_node.inputs[0])
aux_out.file_slots[0].path = "depth_"
tree.links.new(map_node.outputs[0], aux_out.inputs[0])
aux_out.file_slots.new("normal_")
tree.links.new(rl.outputs['Normal'], aux_out.inputs[1])
# --- 2. Exposure bracket LDR output ---
ldr_out = tree.nodes.new('CompositorNodeOutputFile')
ldr_out.format.file_format = 'PNG'
ldr_out.base_path = ""
ldr_out.file_slots.clear()
for i, exp_val in enumerate(CONFIG["EXPOSURES"]):
mix_node = tree.nodes.new('CompositorNodeMixRGB')
mix_node.blend_type = 'MULTIPLY'
mix_node.inputs[2].default_value = (exp_val, exp_val, exp_val, 1)
mix_node.inputs[0].default_value = 1.0
slot_name = f"ldr_exp_{str(i).replace('.', '_')}_"
ldr_out.file_slots.new(slot_name)
tree.links.new(rl.outputs['Image'], mix_node.inputs[1])
tree.links.new(mix_node.outputs[0], ldr_out.inputs[i])
return aux_out, ldr_out
def get_pose_matrix(pitch_deg, yaw_deg, radius):
phi, theta = radians(pitch_deg), radians(yaw_deg)
trans_t = np.array([[1,0,0,0],[0,1,0,0],[0,0,1,radius],[0,0,0,1]], dtype=float)
rot_phi = np.array([[1,0,0,0],[0,np.cos(phi),-np.sin(phi),0],[0,np.sin(phi),np.cos(phi),0],[0,0,0,1]], dtype=float)
rot_theta = np.array([[np.cos(theta),0,np.sin(theta),0],[0,1,0,0],[-np.sin(theta),0,np.cos(theta),0],[0,0,0,1]], dtype=float)
return rot_theta @ (rot_phi @ trans_t)
def save_as_cameras_bin(data, file_path):
if os.path.exists(file_path):
print(f"Already have {file_path}. Skipping...")
return
w = int(data["w"]) # Width
h = int(data["h"]) # Height
fx = data["fl_x"] # Horizontal focal length
fy = data["fl_y"] # Vertical focal length
cx = data["cx"] # Principal point X
cy = data["cy"] # Principal point Y
with open(file_path, "wb") as f:
# A. First write the camera count: 1 camera (format Q represents uint64)
f.write(struct.pack("<Q", 1))
# Set ID to 1 (I), set model to 1 for PINHOLE (i), Width (Q), Height (Q)
f.write(struct.pack("<iiQQ", 1, 1, w, h))
# C. Write the 4 core camera intrinsic parameters: fx, fy, cx, cy (format dddd represents 4 doubles)
f.write(struct.pack("<dddd", fx, fy, cx, cy))
def save_all_frames_to_bin(json_data, bin_path):
flip_mat = mathutils.Matrix.Scale(-1, 4, (0,1,0)) @ mathutils.Matrix.Scale(-1, 4, (0,0,1))
if os.path.exists(bin_path):
f = open(bin_path, "r+b")
total = struct.unpack("<Q", f.read(8))[0]
f.seek(0, 2) # Move to the end of the file
else:
f = open(bin_path, "wb")
f.write(struct.pack("<Q", 0))
total = 0
for frame in json_data["frames"]:
total += 1
m = mathutils.Matrix(frame["transform_matrix"])
w2c = (m @ flip_mat).inverted()
q = w2c.to_quaternion()
t = w2c.translation
# Match the reader exactly: <I dddd ddd I -> 64 bytes
f.write(struct.pack(
"<I dddd ddd I",
total,
q.w, q.x, q.y, q.z,
t.x, t.y, t.z,
1
))
name = os.path.basename(frame["file_path"]) # train_hdr_000.exr
name = name.replace("train_hdr_", "train_ldr_").replace("test_hdr_", "test_ldr_").replace(".exr", "_3.png")
name = name.encode("utf-8") + b"\x00"
# name = os.path.basename(frame["file_path"]).encode("utf-8") + b"\x00"
f.write(name)
f.write(struct.pack("<Q", 0)) # num_points = 0
f.seek(0)
f.write(struct.pack("<Q", total))
f.close()
return
def render_task(is_train=True):
global chosen_tonemap
sub_folder = "train" if is_train else "test"
flag = 1 if is_train else 0
# Resolve outputs from the dataset root, independently of the .blend location.
root_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), CONFIG["RESULTS_PATH"])
setup_environment()
cam = bpy.data.objects['Camera']
bpy.context.scene.camera = cam
bpy.context.scene.frame_set(1)
if cam.animation_data:
cam.animation_data_clear()
aux_node, ldr_node = setup_nodes(root_path)
# Set up the camera rig
if 'Empty' in bpy.data.objects:
bpy.data.objects.remove(bpy.data.objects['Empty'], do_unlink=True)
b_empty = bpy.data.objects.new("Empty", None)
bpy.context.scene.collection.objects.link(b_empty)
cam.parent = b_empty
cam.location = (0, 0, 0)
cam.rotation_euler = (0, 0, 0)
base_matrix = get_pose_matrix(CONFIG["INIT_ROT"][0], CONFIG["INIT_ROT"][1], CONFIG["RADIUS"])
# json_data = {'camera_angle_x': cam.data.angle_x, 'frames': []}
res_x, res_y = bpy.context.scene.render.resolution_x, bpy.context.scene.render.resolution_y
fl_x = (res_x / 2) / math.tan(cam.data.angle_x / 2)
fl_y = (res_y / 2) / math.tan(cam.data.angle_y / 2)
json_data = {
"camera_angle_x": cam.data.angle_x,
"camera_angle_y": cam.data.angle_y,
"fl_x": fl_x,
"fl_y": fl_y,
"cx": res_x / 2,
"cy": res_y / 2,
"w": res_x,
"h": res_y,
'tonemapping': chosen_tonemap, # New field
'look': bpy.context.scene.view_settings.look,
'exposure_bracket': CONFIG["EXPOSURES"],
"frames": []
}
exposure_data = {}
sparse_path = os.path.join(root_path, 'sparse', '0')
os.makedirs(sparse_path, exist_ok=True)
save_as_cameras_bin(json_data, os.path.join(sparse_path, 'cameras.bin'))
count = 0
row_cen, col_cen = (CONFIG["ROWS"]-1)/2, (CONFIG["COLS"]-1)/2
for r in range(CONFIG["ROWS"]):
for c in range(CONFIG["COLS"]):
if (r + c) % 2 == flag: continue
# Calculate the camera pose
curr_pitch = (r - row_cen) * CONFIG["ROT_STEP"] + CONFIG["INIT_ROT"][0]
curr_yaw = (c - col_cen) * CONFIG["ROT_STEP"] + CONFIG["INIT_ROT"][1]
trans_m = get_pose_matrix(curr_pitch, curr_yaw, CONFIG["RADIUS"])
loc_offset = trans_m[:3, 3:] - base_matrix[:3, 3:] + CONFIG["INIT_LOC"]
b_empty.location = (loc_offset[0][0], -loc_offset[2][0], loc_offset[1][0])
b_empty.rotation_euler = (radians(curr_pitch + 90), 0, radians(curr_yaw))
# bpy.context.view_layer.update()
# DEBUG
# b_empty.location = (2.5, 1.437, 0.4669)
# b_empty.rotation_euler = (radians(80.914), 0, radians(-246.58))
# print(b_empty.location)
# print(b_empty.rotation_euler)
# print((curr_pitch + 90, 0, curr_yaw))
# print(cam.location)
# print(cam.rotation_euler)
# print("Camera world position:", cam.matrix_world.to_translation())
# print(cam.data.lens)
# print(cam.data.sensor_width)
# while True:
# pass
# Set output paths
hdr_dir = os.path.join(root_path, 'images_hdr')
img_dir = os.path.join(root_path, 'images')
depth_dir = os.path.join(root_path, 'depth')
normal_dir = os.path.join(root_path, 'normal')
for d in [hdr_dir, img_dir, depth_dir, normal_dir]:
if not os.path.exists(d): os.makedirs(d)
bpy.context.scene.render.filepath = os.path.join(hdr_dir, f"{sub_folder}_hdr_{count:03d}.exr")
ldr_node.base_path = img_dir
for i, exp_val in enumerate(CONFIG["EXPOSURES"]):
slot_filename = f"{sub_folder}_ldr_{count:03d}_{i}_"
ldr_node.file_slots[i].path = slot_filename
slot_filename = f"{sub_folder}_ldr_{count:03d}_{i}.png"
exposure_data[slot_filename] = exp_val
aux_node.base_path = root_path
aux_node.file_slots[0].path = f"depth/{sub_folder}_depth_{count:03d}_" # Automatically save to the depth subfolder
aux_node.file_slots[1].path = f"normal/{sub_folder}_normal_{count:03d}_"
# Render
bpy.ops.render.render(write_still=True)
# Clean up all PNG suffixes in one pass
for folder in [img_dir, depth_dir, normal_dir]:
for f in os.listdir(folder):
if f.endswith("0001.png"):
os.rename(os.path.join(folder, f), os.path.join(folder, f.replace("_0001.png", ".png")))
# Save random information to JSON
json_data['frames'].append({
'file_path': os.path.join(f"{CONFIG['RESULTS_PATH']}", 'images_hdr', f"{sub_folder}_hdr_{count:03d}.exr"),
'transform_matrix': [list(row) for row in cam.matrix_world],
})
count += 1
with open(os.path.join(root_path, f"transforms_{sub_folder}.json"), 'w') as f:
json.dump(json_data, f, indent=4)
save_all_frames_to_bin(json_data, os.path.join(sparse_path, 'images.bin'))
path = os.path.join(root_path, "exposure.json")
json_data = json.load(open(path)) if os.path.exists(path) else {}
json_data.update(exposure_data)
with open(path, "w") as f:
json.dump(json_data, f, indent=4)
if __name__ == "__main__":
update_config_from_camera()
render_task(True)
render_task(False)