Update README.md

README.md

@@ -109,7 +109,7 @@ This dataset is ready for commercial/non-commercial use.
 | Column Name | Description | Data Type |
 |-------------|-------------|-----------|
 | `image_id` | Unique identifier for the image | string |
-| `image_path` | Image file, PIL type | image |
+| `image` | Image file, PIL type | image |
 | `image_title` | Human-written title summarizing the content or subject | string |
 | `image_description` | Human-written narrative describing what is visibly present | string |
 | `scene_description` | Technical and compositional details about image capture | string |
@@ -146,7 +146,7 @@ val_data = load_dataset("Dataseeds/GuruShots-Sample-Dataset-GSD", split="validat
 
 # Access images and annotations
 sample = dataset["train"][0]
-image = sample["image_path"]  # PIL Image object
+image = sample["image"]  # PIL Image object
 title = sample["image_title"]
 description = sample["image_description"]
 segments = sample["segmented_objects"]
@@ -168,7 +168,7 @@ import torch
 dataset = load_dataset("Dataseeds/GuruShots-Sample-Dataset-GSD", split="train")
 
 # Convert to PyTorch format
-dataset.set_format(type="torch", columns=["image_path", "image_title", "segmentation_masks"])
+dataset.set_format(type="torch", columns=["image", "image_title", "segmentation_masks"])
 
 # Create DataLoader
 dataloader = DataLoader(dataset, batch_size=16, shuffle=True)
@@ -185,7 +185,7 @@ dataset = load_dataset("Dataseeds/GuruShots-Sample-Dataset-GSD", split="train")
 
 # Convert to TensorFlow Dataset
 tf_dataset = dataset.to_tf_dataset(
-    columns=["image_path", "image_title"],
+    columns=["image", "image_title"],
     batch_size=16,
     shuffle=True
 )