Upload script.py
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script.py
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### This is example of the script that will be run in the test environment.
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### Some parts of the code are compulsory and you should NOT CHANGE THEM.
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### They are between '''---compulsory---''' comments.
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### You can change the rest of the code to define and test your solution.
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### However, you should not change the signature of the provided function.
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### The script would save "submission.parquet" file in the current directory.
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### The actual logic of the solution is implemented in the `handcrafted_solution.py` file.
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### The `handcrafted_solution.py` file is a placeholder for your solution.
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### You should implement the logic of your solution in that file.
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### You can use any additional files and subdirectories to organize your code.
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'''---compulsory---'''
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# import subprocess
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# from pathlib import Path
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# def install_package_from_local_file(package_name, folder='packages'):
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# """
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# Installs a package from a local .whl file or a directory containing .whl files using pip.
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# Parameters:
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# path_to_file_or_directory (str): The path to the .whl file or the directory containing .whl files.
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# """
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# try:
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# pth = str(Path(folder) / package_name)
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# subprocess.check_call([subprocess.sys.executable, "-m", "pip", "install",
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# "--no-index", # Do not use package index
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# "--find-links", pth, # Look for packages in the specified directory or at the file
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# package_name]) # Specify the package to install
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# print(f"Package installed successfully from {pth}")
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# except subprocess.CalledProcessError as e:
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# print(f"Failed to install package from {pth}. Error: {e}")
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# install_package_from_local_file('hoho')
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import hoho; hoho.setup() # YOU MUST CALL hoho.setup() BEFORE ANYTHING ELSE
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# import subprocess
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# import importlib
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# from pathlib import Path
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# import subprocess
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# ### The function below is useful for installing additional python wheels.
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# def install_package_from_local_file(package_name, folder='packages'):
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# """
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# Installs a package from a local .whl file or a directory containing .whl files using pip.
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# Parameters:
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# path_to_file_or_directory (str): The path to the .whl file or the directory containing .whl files.
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# """
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# try:
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# pth = str(Path(folder) / package_name)
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# subprocess.check_call([subprocess.sys.executable, "-m", "pip", "install",
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# "--no-index", # Do not use package index
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# "--find-links", pth, # Look for packages in the specified directory or at the file
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# package_name]) # Specify the package to install
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# print(f"Package installed successfully from {pth}")
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# except subprocess.CalledProcessError as e:
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# print(f"Failed to install package from {pth}. Error: {e}")
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# pip download webdataset -d packages/webdataset --platform manylinux1_x86_64 --python-version 38 --only-binary=:all:
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# install_package_from_local_file('webdataset')
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# install_package_from_local_file('tqdm')
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### Here you can import any library or module you want.
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### The code below is used to read and parse the input dataset.
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### Please, do not modify it.
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import webdataset as wds
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from tqdm import tqdm
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from typing import Dict
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import pandas as pd
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from transformers import AutoTokenizer
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import os
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import time
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import io
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from PIL import Image as PImage
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import numpy as np
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from hoho.read_write_colmap import read_cameras_binary, read_images_binary, read_points3D_binary
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from hoho import proc, Sample
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def convert_entry_to_human_readable(entry):
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out = {}
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already_good = ['__key__', 'wf_vertices', 'wf_edges', 'edge_semantics', 'mesh_vertices', 'mesh_faces', 'face_semantics', 'K', 'R', 't']
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for k, v in entry.items():
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if k in already_good:
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out[k] = v
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continue
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if k == 'points3d':
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out[k] = read_points3D_binary(fid=io.BytesIO(v))
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if k == 'cameras':
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out[k] = read_cameras_binary(fid=io.BytesIO(v))
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if k == 'images':
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out[k] = read_images_binary(fid=io.BytesIO(v))
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if k in ['ade20k', 'gestalt']:
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out[k] = [PImage.open(io.BytesIO(x)).convert('RGB') for x in v]
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if k == 'depthcm':
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out[k] = [PImage.open(io.BytesIO(x)) for x in entry['depthcm']]
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return out
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'''---end of compulsory---'''
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### The part below is used to define and test your solution.
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from pathlib import Path
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def save_submission(submission, path):
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"""
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Saves the submission to a specified path.
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Parameters:
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submission (List[Dict[]]): The submission to save.
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path (str): The path to save the submission to.
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"""
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sub = pd.DataFrame(submission, columns=["__key__", "wf_vertices", "wf_edges"])
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sub.to_parquet(path)
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print(f"Submission saved to {path}")
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if __name__ == "__main__":
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from handcrafted_solution import predict
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print ("------------ Loading dataset------------ ")
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params = hoho.get_params()
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dataset = hoho.get_dataset(decode=None, split='all', dataset_type='webdataset')
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print('------------ Now you can do your solution ---------------')
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solution = []
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from concurrent.futures import ProcessPoolExecutor
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with ProcessPoolExecutor(max_workers=8) as pool:
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results = []
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for i, sample in enumerate(tqdm(dataset)):
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results.append(pool.submit(predict, sample, visualize=False))
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for i, result in enumerate(tqdm(results)):
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key, pred_vertices, pred_edges = result.result()
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solution.append({
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'__key__': key,
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'wf_vertices': pred_vertices.tolist(),
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'wf_edges': pred_edges
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})
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if i % 100 == 0:
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# incrementally save the results in case we run out of time
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print(f"Processed {i} samples")
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# save_submission(solution, Path(params['output_path']) / "submission.parquet")
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print('------------ Saving results ---------------')
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save_submission(solution, Path(params['output_path']) / "submission.parquet")
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print("------------ Done ------------ ")
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