Upload folder using huggingface_hub

CellCTC/.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

CellCTC/chanage_names.py

@@ -0,0 +1,61 @@
+import os
+
+# Base directory for the annotations
+annotations_dir = "/l/users/sahal.mullappilly/Komal/documents/Cell/CTCdataset/Annotations"
+
+# Function to rename the files in the annotations folder
+def rename_annotation_files():
+    # Walk through the directories and files in the annotations folder
+    for root, dirs, files in os.walk(annotations_dir):
+        for file in files:
+            # Check if the file is a PNG (annotation files)
+            if file.endswith(".png"):
+                # Create a new name based on the current naming pattern
+                base_filename = file.replace("man_track", "t").replace(".png", ".png")  # Rename pattern
+                new_file_path = os.path.join(root, base_filename)
+                
+                # Get the current file path
+                old_file_path = os.path.join(root, file)
+                
+                # Rename the file
+                os.rename(old_file_path, new_file_path)
+                print(f"Renamed {old_file_path} to {new_file_path}")
+
+# Call the function to rename the annotation files
+# rename_annotation_files()
+
+print("All annotation files have been renamed successfully!")
+
+# Directories to process
+jpeg_images_dir = "/l/users/sahal.mullappilly/Komal/documents/Cell/CTCdataset/JPEGImages"
+annotations_dir = "/l/users/sahal.mullappilly/Komal/documents/Cell/CTCdataset/Annotations"
+
+# Function to rename files in a directory
+def rename_files_in_directory(directory):
+    for root, dirs, files in os.walk(directory):
+        for file in files:
+            # Skip if file doesn't have the expected format (adjust this based on your requirements)
+            if file.endswith(".png") or file.endswith(".jpg"):
+                try:
+                    # Extract the numeric part from the filename
+                    num_str = file.lstrip('t').split('.')[0]  # Remove 't' and split on the dot
+                    new_name = f"{num_str}.png" if file.endswith(".png") else f"{num_str}.jpg"
+
+                    # Define the old and new file paths
+                    old_file_path = os.path.join(root, file)
+                    new_file_path = os.path.join(root, new_name)
+
+                    # Rename the file
+                    os.rename(old_file_path, new_file_path)
+                    print(f"Renamed: {old_file_path} -> {new_file_path}")
+
+                except Exception as e:
+                    print(f"Error renaming {file}: {e}")
+
+# Rename files in JPEGImages directory
+rename_files_in_directory(jpeg_images_dir)
+
+# Rename files in Annotations directory
+rename_files_in_directory(annotations_dir)
+
+print("File renaming completed!")

CellCTC/convert_to_jpg.py

@@ -0,0 +1,82 @@
+import os
+from PIL import Image
+import numpy as np
+
+# Base directory for the datasets
+base_dir = "/l/users/sahal.mullappilly/Komal/documents/Cell/CTCdataset"
+
+# List of datasets and their video folder names
+datasets = [
+    {"dataset_name": "BF-C2DL-HSC", "subfolders": ["01", "02"]},
+    {"dataset_name": "BF-C2DL-MuSC", "subfolders": ["01", "02"]},
+    {"dataset_name": "DIC-C2DH-HeLa", "subfolders": ["01", "02"]},
+    {"dataset_name": "Fluo-C2DL-Huh7", "subfolders": ["01", "02"]},
+    {"dataset_name": "Fluo-C2DL-MSC", "subfolders": ["01", "02"]},
+    {"dataset_name": "Fluo-N2DH-GOWT1", "subfolders": ["01", "02"]},
+    {"dataset_name": "Fluo-N2DL-HeLa", "subfolders": ["01", "02"]},
+    {"dataset_name": "PhC-C2DH-U373", "subfolders": ["01", "02"]},
+    {"dataset_name": "PhC-C2DL-PSC", "subfolders": ["01", "02"]},
+    {"dataset_name": "Fluo-N2DH-SIM+", "subfolders": ["01", "02"]}
+]
+
+# Function to convert TIFF to JPG
+def convert_tiff_to_jpg(tiff_path, jpg_path):
+    try:
+        # Open the tiff image using PIL
+        img = Image.open(tiff_path)
+        
+        # Check if image is empty
+        if img.size == (0, 0):
+            print(f"Warning: {tiff_path} is empty. Skipping this file.")
+            return
+        
+        # Check for bit depth and convert to 8-bit if necessary (normalize if > 8-bit)
+        if img.mode != 'RGB':
+            img = img.convert('RGB')  # Convert to RGB if not already in that mode
+
+        # Convert the image to a NumPy array to normalize pixel values if necessary
+        img_array = np.array(img)
+        
+        # Normalize if pixel values are outside the range of [0, 255] (for 16-bit or higher)
+        if img_array.max() > 255:
+            img_array = (img_array / img_array.max()) * 255  # Normalize to 0-255 range
+            img_array = img_array.astype(np.uint8)
+
+        # Save the image as JPG
+        img = Image.fromarray(img_array)
+        img.save(jpg_path, 'JPEG')
+        print(f"Converted {tiff_path} to {jpg_path}")
+    except Exception as e:
+        print(f"Error converting {tiff_path}: {e}")
+
+# Function to process dataset
+def process_dataset(dataset_name, subfolders):
+    # Path for the main "JPEGImages" folder where all images will be stored
+    main_jpeg_dir = os.path.join(base_dir, "JPEGImages")
+    os.makedirs(main_jpeg_dir, exist_ok=True)
+
+    for subfolder in subfolders:
+        # Paths for the subfolder
+        input_folder = os.path.join(base_dir, "datasets", dataset_name, subfolder)
+        output_folder = os.path.join(main_jpeg_dir, f"{dataset_name}-{subfolder}")
+        
+        # Create output directory for each subfolder inside "JPEGImages"
+        os.makedirs(output_folder, exist_ok=True)
+
+        # Process each .tif file in the subfolder
+        for root, dirs, files in os.walk(input_folder):
+            for file in files:
+                if file.endswith(".tif"):
+                    tiff_path = os.path.join(root, file)
+                    # Define the path for the new jpg file
+                    jpg_filename = file.replace(".tif", ".jpg")
+                    jpg_path = os.path.join(output_folder, jpg_filename)
+                    
+                    # Convert .tif to .jpg
+                    convert_tiff_to_jpg(tiff_path, jpg_path)
+
+# Process each dataset
+for dataset in datasets:
+    process_dataset(dataset["dataset_name"], dataset["subfolders"])
+
+print("All TIFF images converted to JPG and saved in the 'JPEGImages' folder!")

CellCTC/download.py

@@ -0,0 +1,90 @@
+import os
+import requests
+from tqdm import tqdm
+
+# Define the dataset details
+datasets = [
+    {
+        "name": "BF-C2DL-HSC",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/BF-C2DL-HSC.zip",
+        "size": "1.6 GB"
+    },
+    {
+        "name": "BF-C2DL-MuSC",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/BF-C2DL-MuSC.zip",
+        "size": "1.2 GB"
+    },
+    {
+        "name": "DIC-C2DH-HeLa",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/DIC-C2DH-HeLa.zip",
+        "size": "37 MB"
+    },
+    {
+        "name": "Fluo-C2DL-Huh7",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/Fluo-C2DL-Huh7.zip",
+        "size": "36 MB"
+    },
+    {
+        "name": "Fluo-C2DL-MSC",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/Fluo-C2DL-MSC.zip",
+        "size": "72 MB"
+    },
+    {
+        "name": "Fluo-N2DH-GOWT1",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/Fluo-N2DH-GOWT1.zip",
+        "size": "53 MB"
+    },
+    {
+        "name": "Fluo-N2DL-HeLa",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/Fluo-N2DL-HeLa.zip",
+        "size": "182 MB"
+    },
+    {
+        "name": "PhC-C2DH-U373",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/PhC-C2DH-U373.zip",
+        "size": "40 MB"
+    },
+    {
+        "name": "PhC-C2DL-PSC",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/PhC-C2DL-PSC.zip",
+        "size": "124 MB"
+    },
+    {
+        "name": "Fluo-N2DH-SIM+",
+        "url": "http://data.celltrackingchallenge.net/training-datasets/Fluo-N2DH-SIM+.zip",
+        "size": "91 MB"
+    }
+]
+
+# Directory where you want to save the datasets
+base_dir = "./CTCdataset"
+
+# Function to download dataset
+def download_dataset(url, save_path):
+    print(f"Downloading {url} to {save_path}")
+    response = requests.get(url, stream=True)
+    total_size = int(response.headers.get('Content-Length', 0))
+    with open(save_path, 'wb') as f:
+        with tqdm(total=total_size, unit='B', unit_scale=True) as pbar:
+            for chunk in response.iter_content(chunk_size=1024):
+                if chunk:
+                    f.write(chunk)
+                    pbar.update(len(chunk))
+
+# Create the base directory if it doesn't exist
+os.makedirs(base_dir, exist_ok=True)
+
+# Download all datasets
+for dataset in datasets:
+    dataset_dir = os.path.join(base_dir, dataset["name"])
+    os.makedirs(dataset_dir, exist_ok=True)
+    
+    # Define the path where the zip file will be saved
+    zip_file_path = os.path.join(dataset_dir, f"{dataset['name']}.zip")
+    
+    # Download the dataset
+    download_dataset(dataset["url"], zip_file_path)
+
+    print(f"Dataset {dataset['name']} downloaded successfully!")
+
+print("All datasets downloaded successfully!")

CellCTC/extract.py

@@ -0,0 +1,39 @@
+import os
+import zipfile
+
+# Define the dataset names
+datasets = [
+    "BF-C2DL-HSC",
+    "BF-C2DL-MuSC",
+    "DIC-C2DH-HeLa",
+    "Fluo-C2DL-Huh7",
+    "Fluo-C2DL-MSC",
+    "Fluo-N2DH-GOWT1",
+    "Fluo-N2DL-HeLa",
+    "PhC-C2DH-U373",
+    "PhC-C2DL-PSC",
+    "Fluo-N2DH-SIM+"
+]
+
+# Directory where the datasets are stored
+base_dir = "/l/users/sahal.mullappilly/Komal/documents/Cell/CTCdataset"
+
+# Function to extract dataset
+def extract_zip(zip_path, extract_to):
+    print(f"Extracting {zip_path} to {extract_to}")
+    with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+        zip_ref.extractall(extract_to)
+    print(f"Extraction complete for {zip_path}!")
+
+# Extract all datasets
+for dataset in datasets:
+    dataset_dir = os.path.join(base_dir, dataset)
+    zip_file_path = os.path.join(dataset_dir, f"{dataset}.zip")
+    
+    # Extract the dataset
+    if os.path.exists(zip_file_path):
+        extract_zip(zip_file_path, dataset_dir)
+    else:
+        print(f"Zip file for {dataset} not found!")
+
+print("All datasets extracted successfully!")