Delete script.py

script.py

@@ -1,297 +0,0 @@
-### This is example of the script that will be run in the test environment.
-### Some parts of the code are compulsory and you should NOT CHANGE THEM.
-### They are between '''---compulsory---''' comments.
-### You can change the rest of the code to define and test your solution.
-### However, you should not change the signature of the provided function.
-### The script would save "submission.parquet" file in the current directory.
-### The actual logic of the solution is implemented in the `handcrafted_solution.py` file.
-### The `handcrafted_solution.py` file is a placeholder for your solution.
-### You should implement the logic of your solution in that file.
-### You can use any additional files and subdirectories to organize your code.
-
-'''---compulsory---'''
-# 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')
-
-### Here you can import any library or module you want.
-### The code below is used to read and parse the input dataset.
-### Please, do not modify it.
-
-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
-
-'''---end of compulsory---'''
-
-### The part below is used to define and test your solution.
-import subprocess
-import sys
-import os
-
-import numpy as np
-os.environ['MKL_THREADING_LAYER'] = 'GNU'
-os.environ['MKL_SERVICE_FORCE_INTEL'] = '1'
-
-def uninstall_package(package_name):
-	"""
-	Uninstalls a package using pip.
-
-	Parameters:
-	package_name (str): The name of the package to uninstall.
-	"""
-	try:
-		subprocess.check_call([sys.executable, "-m", "pip", "uninstall", "-y", package_name])
-		print(f"Package {package_name} uninstalled successfully")
-	except subprocess.CalledProcessError as e:
-		print(f"Failed to uninstall package {package_name}. Error: {e}")
-
-# def download_packages(packages, folder='packages/torch'):
-# 	"""
-# 	Downloads packages as .whl files into the specified folder using pip.
-
-# 	Parameters:
-# 	packages (list): List of packages to download with versions.
-# 	folder (str): The folder where the .whl files will be saved.
-# 	"""
-# 	Path(folder).mkdir(parents=True, exist_ok=True)
-# 	try:
-# 		subprocess.check_call([sys.executable, "-m", "pip", "download",
-# 							   "--platform", "manylinux1_x86_64",
-# 							   "--python-version", "38",
-# 							   "--only-binary=:all:",
-# 							   "-d", folder] + packages)
-# 		print(f"Packages downloaded successfully into {folder}")
-# 	except subprocess.CalledProcessError as e:
-# 		print(f"Failed to download packages. Error: {e}")
-
-def download_packages(packages, folder):
-	# Create the directory if it doesn't exist
-	if not os.path.exists(folder):
-		os.makedirs(folder)
-	
-	try:
-		subprocess.check_call([
-			'pip', 'download',
-			'--dest', folder,
-			'-f', 'https://download.pytorch.org/whl/cu121'
-		] + packages)
-		print(f"Packages downloaded successfully to {folder}")
-	except subprocess.CalledProcessError as e:
-		print(f"Failed to download packages. Error: {e}")
-
-# Set CUDA environment variables
-os.environ['CUDA_HOME'] = '/usr/local/cuda'
-os.environ['PATH'] = os.environ['CUDA_HOME'] + '/bin:' + os.environ['PATH']
-os.environ['LD_LIBRARY_PATH'] = os.environ['CUDA_HOME'] + '/lib64:' + os.environ.get('LD_LIBRARY_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:
-	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 install_which():
-	try:
-		# Attempt to install which if it's not available
-		subprocess.check_call(['sudo', 'apt-get', 'install', '-y', 'which'])
-		print("Which installed successfully.")
-	except subprocess.CalledProcessError as e:
-		print(f"An error occurred while installing which: {e}")
-		sys.exit(1)
-		
-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')
-	# install_package_from_local_file('ninja', folder='packages')
-	# download_packages(['scikit-learn'], folder='packages/scikit-learn')
-	# download_packages(['open3d'], folder='packages/open3d')
-	# download_packages(['easydict'], folder='packages/easydict')
-	
-	# try:
-	# 	subprocess.check_call(['which', 'which'])
-	# except subprocess.CalledProcessError:
-	# 	install_which()
-	
-	pc_util_path = os.path.join(os.getcwd(), 'pc_util')
-	if os.path.isdir(pc_util_path):
-		os.chdir(pc_util_path)
-		subprocess.check_call([sys.executable, "setup.py", "install"], cwd=pc_util_path)
-		os.chdir("..")
-	
-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', '')}"
-
-	os.environ['PATH'] = '/usr/local/cuda/bin'
-	os.environ['LD_LIBRARY_PATH'] = '/usr/local/cuda/lib64'  
-	os.environ['LIBRARY_PATH'] = '/usr/local/cuda/lib64'
-
-	# usr_local_contents = os.listdir('/usr/local')
-	# # print("Items under /usr/local:")
-	# for item in usr_local_contents:
-	# 	print(item)
-
-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}")
-
-if __name__ == "__main__":
-	# setup_cuda_environment()
-	setup_environment()
-
-	from handcrafted_solution import predict
-	print ("------------ Loading dataset------------ ")
-	params = hoho.get_params()
-	dataset = hoho.get_dataset(decode=None, split='all', dataset_type='webdataset')
-
-	print('------------ Now you can do your solution ---------------')
-	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
-				print(f"Processed {i} samples")
-				# save_submission(solution, Path(params['output_path']) / "submission.parquet")
-	print('------------ Saving results ---------------')
-	save_submission(solution, Path(params['output_path']) / "submission.parquet")
-	print("------------ Done ------------ ")