app.py

# import subprocess
# from pathlib import Path         
# def install_package_from_local_file(package_name, folder='packages'):
#     """
#     Installs a package from a local .whl file or a directory containing .whl files using pip.

#     Parameters:
#     path_to_file_or_directory (str): The path to the .whl file or the directory containing .whl files.
#     """
#     try:
#         pth = str(Path(folder) / package_name)
#         subprocess.check_call([subprocess.sys.executable, "-m", "pip", "install", 
#                                "--no-index",  # Do not use package index
#                                "--find-links", pth,  # Look for packages in the specified directory or at the file
#                                package_name])  # Specify the package to install
#         print(f"Package installed successfully from {pth}")
#     except subprocess.CalledProcessError as e:
#         print(f"Failed to install package from {pth}. Error: {e}")
		
# install_package_from_local_file('hoho')

import hoho; hoho.setup() # YOU MUST CALL hoho.setup() BEFORE ANYTHING ELSE
# import subprocess
# import importlib
# from pathlib import Path
# import subprocess


# ### The function below is useful for installing additional python wheels.        
# def install_package_from_local_file(package_name, folder='packages'):
#     """
#     Installs a package from a local .whl file or a directory containing .whl files using pip.

#     Parameters:
#     path_to_file_or_directory (str): The path to the .whl file or the directory containing .whl files.
#     """
#     try:
#         pth = str(Path(folder) / package_name)
#         subprocess.check_call([subprocess.sys.executable, "-m", "pip", "install", 
#                                "--no-index",  # Do not use package index
#                                "--find-links", pth,  # Look for packages in the specified directory or at the file
#                                package_name])  # Specify the package to install
#         print(f"Package installed successfully from {pth}")
#     except subprocess.CalledProcessError as e:
#         print(f"Failed to install package from {pth}. Error: {e}")
		

# pip download webdataset -d packages/webdataset --platform manylinux1_x86_64 --python-version 38 --only-binary=:all:
# install_package_from_local_file('webdataset')
# install_package_from_local_file('tqdm')

import streamlit as st
import webdataset as wds
from tqdm import tqdm
from typing import Dict
import pandas as pd
from transformers import AutoTokenizer
import os
import time
import io
from PIL import Image as PImage
import numpy as np

from hoho.read_write_colmap import read_cameras_binary, read_images_binary, read_points3D_binary
from hoho import proc, Sample

def convert_entry_to_human_readable(entry):
	out = {}
	already_good = ['__key__', 'wf_vertices', 'wf_edges', 'edge_semantics', 'mesh_vertices', 'mesh_faces', 'face_semantics', 'K', 'R', 't']
	for k, v in entry.items():
		if k in already_good:
			out[k] = v
			continue
		if k == 'points3d':
			out[k] = read_points3D_binary(fid=io.BytesIO(v))
		if k == 'cameras':
			out[k] = read_cameras_binary(fid=io.BytesIO(v))
		if k == 'images':
			out[k] = read_images_binary(fid=io.BytesIO(v))
		if k in ['ade20k', 'gestalt']:
			out[k] =  [PImage.open(io.BytesIO(x)).convert('RGB') for x in v]
		if k == 'depthcm':
			out[k] = [PImage.open(io.BytesIO(x)) for x in entry['depthcm']]
	return out

import subprocess
import sys
import os

import numpy as np
os.environ['MKL_THREADING_LAYER'] = 'GNU'
os.environ['MKL_SERVICE_FORCE_INTEL'] = '1'

def install_package_from_local_file(package_name, folder='packages'):
	"""
	Installs a package from a local .whl file or a directory containing .whl files using pip.

	Parameters:
	package_name (str): The name of the package to install.
	folder (str): The folder where the .whl files are located.
	"""
	try:
		pth = str(Path(folder) / package_name)
		subprocess.check_call([sys.executable, "-m", "pip", "install", 
							   "--no-index",  # Do not use package index
							   "--find-links", pth,  # Look for packages in the specified directory or at the file
							   package_name])  # Specify the package to install
		print(f"Package installed successfully from {pth}")
	except subprocess.CalledProcessError as e:
		print(f"Failed to install package from {pth}. Error: {e}")

def setup_environment():
	# Uninstall torch if it is already installed
	# packages_to_uninstall = ['torch', 'torchvision', 'torchaudio']
	# for package in packages_to_uninstall:
	# 	uninstall_package(package)
	# Download required packages
	# pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116
	# pip install torch==2.3.0 torchvision==0.18.0 torchaudio==2.3.0 --index-url https://download.pytorch.org/whl/cu121
	# pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu121
	# packages_to_download = ['torch==1.13.1', 'torchvision==0.14.1', 'torchaudio==0.13.1']
	# packages_to_download = ['torch==2.1.0', 'torchvision==0.16.0', 'torchaudio==2.1.0']
	# download_packages(packages_to_download, folder='packages/torch')

	# Install ninja
	# install_package_from_local_file('ninja', folder='packages')

	# packages_to_download = ['torch==2.1.0', 'torchvision==0.16.0', 'torchaudio==2.1.0']
	# download_folder = 'packages/torch'

	# Download the packages
	# download_packages(packages_to_download, download_folder)

	# Install packages from local files
	# install_package_from_local_file('torch', folder='packages')
	# install_package_from_local_file('packages/torch/torchvision-0.16.0-cp38-cp38-manylinux1_x86_64.whl', folder='packages/torch')
	# install_package_from_local_file('packages/torch/torchaudio-2.1.0-cp38-cp38-manylinux1_x86_64.whl', folder='packages/torch')
	# install_package_from_local_file('scikit-learn', folder='packages')
	# install_package_from_local_file('open3d', folder='packages')
	install_package_from_local_file('easydict', folder='packages')
	install_package_from_local_file('setuptools', folder='packages')
	# download_packages(['scikit-learn'], folder='packages/scikit-learn')
	# download_packages(['open3d'], folder='packages/open3d')
	# download_packages(['easydict'], folder='packages/easydict')

	pc_util_path = os.path.join(os.getcwd(), 'pc_util')
	st.write(f"The path to pc_util is {pc_util_path}")
	if os.path.isdir(pc_util_path):
		os.chdir(pc_util_path)
		st.write(f"Installing pc_util from {pc_util_path}")
		subprocess.check_call([sys.executable, "setup.py", "install"])
		st.write("pc_util installed successfully")
		os.chdir("..")
		st.write(f"Current directory is {os.getcwd()}")
	else:
		st.write(f"Directory {pc_util_path} does not exist")
	
	setup_cuda_environment()

def setup_cuda_environment():
	cuda_home = '/usr/local/cuda/'
	if not os.path.exists(cuda_home):
		raise EnvironmentError(f"CUDA_HOME directory {cuda_home} does not exist. Please install CUDA and set CUDA_HOME environment variable.")
	os.environ['CUDA_HOME'] = cuda_home
	os.environ['PATH'] = f"{cuda_home}/bin:{os.environ['PATH']}"
	os.environ['LD_LIBRARY_PATH'] = f"{cuda_home}/lib64:{os.environ.get('LD_LIBRARY_PATH', '')}"
	print(f"CUDA env setup: {cuda_home}")

from pathlib import Path
def save_submission(submission, path):
	"""
	Saves the submission to a specified path.

	Parameters:
	submission (List[Dict[]]): The submission to save.
	path (str): The path to save the submission to.
	"""
	sub = pd.DataFrame(submission, columns=["__key__", "wf_vertices", "wf_edges"])
	sub.to_parquet(path)
	print(f"Submission saved to {path}")
	
def main():
	st.title("Hugging Face Space Prediction App")
	
	# Setting up environment
	st.write("Setting up the environment...")
	# setup_environment()
	try:
		setup_environment()
	except Exception as e:
		st.error(f"Env Setup failed: {e}")
		return

	usr_local_contents = os.listdir('/usr/local')
	# print("Items under /usr/local:")
	for item in usr_local_contents:
		st.write(item)

	# Print CUDA path
	cuda_home = os.environ.get('CUDA_HOME', 'CUDA_HOME is not set')
	st.write(f"CUDA_HOME: {cuda_home}")
	st.write(f"PATH: {os.environ.get('PATH', 'PATH is not set')}")
	st.write(f"LD_LIBRARY_PATH: {os.environ.get('LD_LIBRARY_PATH', 'LD_LIBRARY_PATH is not set')}")

	# export PATH=$PATH:/usr/local/cuda/bin  
	# export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64  
	# export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/cuda/lib64

	from handcrafted_solution import predict
	st.write("Loading dataset...")
	
	params = hoho.get_params()
	dataset = hoho.get_dataset(decode=None, split='all', dataset_type='webdataset')

	st.write('Running predictions...')
	solution = []
	from concurrent.futures import ProcessPoolExecutor
	with ProcessPoolExecutor(max_workers=8) as pool:
		results = []
		for i, sample in enumerate(tqdm(dataset)):
			results.append(pool.submit(predict, sample, visualize=False))
		
		for i, result in enumerate(tqdm(results)):
			key, pred_vertices, pred_edges = result.result()
			solution.append({
				'__key__': key,
				'wf_vertices': pred_vertices.tolist(),
				'wf_edges': pred_edges
			})
			if i % 100 == 0:
				# Incrementally save the results in case we run out of time
				st.write(f"Processed {i} samples")
	
	st.write('Saving results...')
	save_submission(solution, Path(params['output_path']) / "submission.parquet")
	st.write("Done!")
	
if __name__ == "__main__":
	main()