delete reorganize_sprite_dataset.py (replaced by generate_sprite_metadata.py)

reorganize_sprite_dataset.py

@@ -1,59 +0,0 @@
-import os
-from datasets import Dataset, DatasetDict, Image, Features, Value
-import glob
-
-# Define the path to your dataset (where the folders like 0_frames, 1_frames, etc., are located)
-dataset_path = "/Users/lorenzo/Documents/GitHub/sprite-animation/train"  # Replace with the actual path
-
-# Define the features for the dataset
-features = Features({
-    "image": Image(),
-    "label": Value("string"),  # The folder name (e.g., "12_frames")
-    "sprite_id": Value("string"),  # The sprite ID (e.g., "12")
-})
-
-# Initialize lists to hold the consolidated data
-images = []
-labels = []
-sprite_ids = []
-
-# Iterate over each folder (0_frames, 1_frames, etc.)
-for folder_name in os.listdir(dataset_path):
-    folder_path = os.path.join(dataset_path, folder_name)
-    
-    # Skip non-directory files and hidden directories (e.g., .git)
-    if not os.path.isdir(folder_path) or folder_name.startswith("."):
-        continue
-
-    print(f"Processing folder: {folder_name}")  # Debug: Print folder being processed
-
-    # Extract the sprite ID from the folder name (e.g., "12" from "12_frames")
-    sprite_id = folder_name.split("_")[0]
-
-    # Load all images in the folder
-    image_paths = glob.glob(os.path.join(folder_path, "sprite_*.png"))
-    print(f"Found {len(image_paths)} images in folder '{folder_name}'")  # Debug: Print number of images found
-
-    for image_path in image_paths:
-        # Append data to the consolidated lists
-        images.append(image_path)
-        labels.append(folder_name)  # Use the folder name as the label
-        sprite_ids.append(sprite_id)  # Use the sprite ID as an additional field
-
-# Create a single dataset with all the data
-dataset = Dataset.from_dict(
-    {
-        "image": images,
-        "label": labels,
-        "sprite_id": sprite_ids,
-    },
-    features=features
-)
-
-# Create a DatasetDict with a single split (e.g., "train")
-final_dataset = DatasetDict({"train": dataset})
-
-# Push the dataset to Hugging Face
-final_dataset.push_to_hub("Lod34/sprite-animation", private=False)  # Set private=True if you want it private
-
-print("Dataset successfully uploaded!")