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# misc.py file contains miscellaneous utility functions | |
import math | |
import sys | |
import logging | |
import os | |
import subprocess | |
from utils.constants import TMPDIR, MAX_SEED | |
import numpy as np | |
def get_output_name(input_image=None, output_image=None, overlay_image=None, bordered_image_output=None): | |
""" | |
Check input_image, output_image, overlay_image, bordered_image_output to find a filename | |
other than None or generic 'image.PNG' and return the filename without extension to use as output_name | |
Args: | |
input_image (str): Path to input image | |
output_image (str): Path to output image | |
overlay_image (str): Path to overlay image | |
bordered_image_output (str): Path to bordered image output | |
Returns: | |
str: Base filename without extension to use as output name, or 'hexagrid_output' if none found | |
""" | |
# Check each input in priority order | |
for image_path in [bordered_image_output, overlay_image, output_image, input_image]: | |
if image_path and isinstance(image_path, str) and get_filename_from_path(image_path.lower()) != "image.png": | |
# Get the filename without path or extension | |
base_name = get_filename_from_path(image_path) | |
name_without_ext = os.path.splitext(base_name)[0] | |
# Filter out temporary filenames that start with tmp or have random hex strings | |
if not (name_without_ext.startswith("tmp") or | |
(len(name_without_ext) >= 8 and all(c in '0123456789abcdef' for c in name_without_ext))): | |
return name_without_ext | |
# Default name if no suitable filename found | |
return "hexagrid_output" | |
def get_filename_from_path(file_path): | |
"""Extract filename from file path.""" | |
if file_path is None: | |
return "" | |
import os | |
return os.path.basename(file_path) | |
def pause(): | |
""" | |
Pauses the execution until any key is pressed. | |
""" | |
if sys.platform.startswith('win'): | |
import msvcrt | |
print("Press any key to continue...") | |
msvcrt.getch() | |
else: | |
import termios | |
import tty | |
print("Press any key to continue...") | |
fd = sys.stdin.fileno() | |
old_settings = termios.tcgetattr(fd) | |
try: | |
tty.setraw(fd) | |
sys.stdin.read(1) | |
finally: | |
termios.tcsetattr(fd, termios.TCSADRAIN, old_settings) | |
def install(package): | |
import subprocess | |
subprocess.check_call([sys.executable, "-m", "pip", "install", package]) | |
def get_filename(file): | |
filename = None | |
if file is not None: | |
filename = file.name | |
return filename | |
def get_extension(file): | |
extension = None | |
if file is not None: | |
extension = file.name.split(".")[-1] | |
return extension | |
def convert_ratio_to_dimensions(ratio, height=512, rotate90=False): | |
""" | |
Calculate pixel dimensions based on a given aspect ratio and base height. | |
This function computes the width and height in pixels for an image, ensuring that both dimensions are divisible by 16. The height is adjusted upwards to the nearest multiple of 16 if necessary, and the width is calculated based on the adjusted height and the provided aspect ratio. Additionally, it ensures that both width and height are at least 16 pixels to avoid extremely small dimensions. | |
Parameters: | |
ratio (float): The aspect ratio of the image (width divided by height). | |
height (int, optional): The base height in pixels. Defaults to 512. | |
Returns: | |
tuple: A tuple containing the calculated (width, height) in pixels, both divisible by 16. | |
""" | |
base_height = 512 | |
# Scale the height based on the provided height parameter | |
# Ensure the height is at least base_height | |
scaled_height = max(height, base_height) | |
# Adjust the height to be divisible by 16 | |
adjusted_height = math.ceil(scaled_height / 16) * 16 | |
# Calculate the width based on the ratio | |
calculated_width = int(adjusted_height * ratio) | |
# Adjust the width to be divisible by 16 | |
adjusted_width = math.ceil(calculated_width / 16) * 16 | |
if rotate90: | |
adjusted_width, adjusted_height = adjusted_height, adjusted_width | |
return adjusted_width, adjusted_height | |
def update_dimensions_on_ratio(aspect_ratio_str, base_height): | |
# Convert aspect_ratio from a string in format "W:H" into numbers and compute new dimensions. | |
width_ratio, height_ratio = map(int, aspect_ratio_str.split(":")) | |
aspect_ratio = width_ratio / height_ratio | |
new_width, new_height = convert_ratio_to_dimensions(aspect_ratio, base_height) | |
return new_width, new_height | |
def install_torch(): | |
print("\nInstalling PyTorch with CUDA support...") | |
# Define the package and index URL | |
package = "torch==2.4.0" | |
index_url = "https://download.pytorch.org/whl/cu124" | |
# Construct the pip install command | |
command = [ | |
"pip", "install", "--force-reinstall", | |
f"{package}", "--index-url", f"{index_url}" | |
] | |
# Run the command using subprocess | |
subprocess.run(command, check=True) | |
print("\nPyTorch installation completed.") | |
print("\nInstalling torchvision...") | |
package = "torchvision==0.19.0" | |
index_url = "https://download.pytorch.org/whl/cu124" | |
# Construct the pip install command | |
command = [ | |
"pip", "install", "--force-reinstall", | |
f"{package}", "--index-url", f"{index_url}" | |
] | |
# Run the command using subprocess | |
subprocess.run(command, check=True) | |
print("\nPlease restart the kernel to use the newly installed PyTorch version.") | |
def _get_output(cmd): | |
try: | |
return subprocess.check_output(cmd).decode("utf-8") | |
except Exception as ex: | |
logging.exception(ex) | |
return None | |
def install_cuda_toolkit(): | |
#CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run" | |
# CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/12.2.0/local_installers/cuda_12.2.0_535.54.03_linux.run" | |
CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run" | |
CUDA_TOOLKIT_FILE = "/tmp/%s" % os.path.basename(CUDA_TOOLKIT_URL) | |
print("\nDownloading CUDA Toolkit from %s" % CUDA_TOOLKIT_URL) | |
subprocess.call(["wget", "-q", CUDA_TOOLKIT_URL, "-O", CUDA_TOOLKIT_FILE]) | |
subprocess.call(["chmod", "+x", CUDA_TOOLKIT_FILE]) | |
subprocess.call([CUDA_TOOLKIT_FILE, "--silent", "--toolkit"]) | |
os.environ["CUDA_HOME"] = "/usr/local/cuda" | |
os.environ["PATH"] = "%s/bin:%s" % (os.environ["CUDA_HOME"], os.environ["PATH"]) | |
os.environ["LD_LIBRARY_PATH"] = "%s/lib:%s" % ( | |
os.environ["CUDA_HOME"], | |
"" if "LD_LIBRARY_PATH" not in os.environ else os.environ["LD_LIBRARY_PATH"], | |
) | |
# Fix: arch_list[-1] += '+PTX'; IndexError: list index out of range | |
os.environ["TORCH_CUDA_ARCH_LIST"] = "8.0;8.6" | |
print("\nPlease restart the kernel to use the newly installed CUDA Toolkit.") | |
def setup_runtime_env(): | |
from torch import cuda | |
logging.info("Python Version: %s" % _get_output(["python", "--version"])) | |
logging.info("CUDA Version: %s" % _get_output(["nvcc", "--version"])) | |
logging.info("GCC Version: %s" % _get_output(["gcc", "--version"])) | |
logging.info("CUDA is available: %s" % cuda.is_available()) | |
logging.info("CUDA Device Capability: %s" % (cuda.get_device_capability(),)) | |
# Install Pre-compiled CUDA extensions (Fallback to this solution on 12/31/24) | |
# Ref: https://huggingface.co/spaces/zero-gpu-explorers/README/discussions/110 | |
##ext_dir = os.path.join(os.path.dirname(__file__), "wheels") | |
##for e in os.listdir(ext_dir): | |
## logging.info("Installing Extensions from %s" % e) | |
## subprocess.call( | |
## ["pip", "install", os.path.join(ext_dir, e)], stderr=subprocess.STDOUT | |
## ) | |
# Compile CUDA extensions | |
# Update on 12/31/24: No module named 'torch'. But it is installed and listed by `pip list` | |
# ext_dir = os.path.join(os.path.dirname(__file__), "citydreamer", "extensions") | |
# for e in os.listdir(ext_dir): | |
# if os.path.isdir(os.path.join(ext_dir, e)): | |
# subprocess.call(["pip", "install", "."], cwd=os.path.join(ext_dir, e)) | |
#logging.info("Installed Python Packages: %s" % _get_output(["pip", "list"])) | |
def get_seed(randomize_seed: bool, seed: int) -> int: | |
""" | |
Get the random seed. | |
""" | |
return np.random.randint(0, MAX_SEED) if randomize_seed else seed | |
def number_to_letter(n: int, upper_case: bool = True): | |
result = '' | |
a_char = 97 | |
if upper_case: | |
a_char -= 32 | |
while abs(n) > 0: | |
n, remainder = divmod(abs(n) - 1, 26) | |
result = chr(a_char + remainder) + result | |
return result |