fix inden err

script.py

@@ -28,7 +28,7 @@
 #         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
@@ -55,7 +55,7 @@ import hoho; hoho.setup() # YOU MUST CALL hoho.setup() BEFORE ANYTHING ELSE
 #         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')
@@ -80,23 +80,23 @@ from hoho.read_write_colmap import read_cameras_binary, read_images_binary, read
 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
+	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---'''
 
@@ -106,109 +106,109 @@ import sys
 import os
 
 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}")
+	"""
+	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 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}")
+	"""
+	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():
-    subprocess.check_call([sys.executable, "-m", "pip", "install", "git+http://hf.co/usm3d/tools.git"])
-    import hoho
-    hoho.setup()
-
-    # Download required packages
-    packages_to_download = ['torch==2.0.1', 'torchvision==0.15.2', 'torchaudio==2.0.2']
-    download_packages(packages_to_download, folder='packages/torch')
-
-    # Install packages from local files
-    install_package_from_local_file('torch', folder='packages/torch')
-    install_package_from_local_file('torchvision', folder='packages/torch')
-    install_package_from_local_file('torchaudio', folder='packages/torch')
-
-    subprocess.check_call([sys.executable, "-m", "pip", "install", "scikit-learn"])
-    subprocess.check_call([sys.executable, "-m", "pip", "install", "tqdm"])
-    subprocess.check_call([sys.executable, "-m", "pip", "install", "scipy"])
-    subprocess.check_call([sys.executable, "-m", "pip", "install", "open3d"])
-    subprocess.check_call([sys.executable, "-m", "pip", "install", "easydict"])
-
-    # 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"])
-    # else:
-    #     print(f"Directory {pc_util_path} does not exist")
-    
+	subprocess.check_call([sys.executable, "-m", "pip", "install", "git+http://hf.co/usm3d/tools.git"])
+	import hoho
+	hoho.setup()
+
+	# Download required packages
+	packages_to_download = ['torch==2.0.1', 'torchvision==0.15.2', 'torchaudio==2.0.2']
+	download_packages(packages_to_download, folder='packages/torch')
+
+	# Install packages from local files
+	install_package_from_local_file('torch', folder='packages/torch')
+	install_package_from_local_file('torchvision', folder='packages/torch')
+	install_package_from_local_file('torchaudio', folder='packages/torch')
+
+	subprocess.check_call([sys.executable, "-m", "pip", "install", "scikit-learn"])
+	subprocess.check_call([sys.executable, "-m", "pip", "install", "tqdm"])
+	subprocess.check_call([sys.executable, "-m", "pip", "install", "scipy"])
+	subprocess.check_call([sys.executable, "-m", "pip", "install", "open3d"])
+	subprocess.check_call([sys.executable, "-m", "pip", "install", "easydict"])
+
+	# 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"])
+	# else:
+	#     print(f"Directory {pc_util_path} does not exist")
+	
 from pathlib import Path
 def save_submission(submission, path):
-    """
-    Saves the submission to a specified 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}")
+	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_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 ------------ ")
+	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 ------------ ")