Update README.md

README.md

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----
-license: mit
-configs:
-- config_name: default
-  data_files:
-  - split: original
-    path: data/original-*
-  - split: augmented
-    path: data/augmented-*
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: label
-    dtype:
-      class_label:
-        names:
-          '0': food
-          '1': view
-  splits:
-  - name: original
-    num_bytes: 371487.0
-    num_examples: 32
-  - name: augmented
-    num_bytes: 4075054.0
-    num_examples: 352
-  download_size: 4411701
-  dataset_size: 4446541.0
----
+---
+license: mit
+configs:
+- config_name: default
+  data_files:
+  - split: original
+    path: data/original-*
+  - split: augmented
+    path: data/augmented-*
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': food
+          '1': view
+  splits:
+  - name: original
+    num_bytes: 371487.0
+    num_examples: 32
+  - name: augmented
+    num_bytes: 4075054.0
+    num_examples: 352
+  download_size: 4411701
+  dataset_size: 4446541.0
+---
+
+
+# 📄 Model Card: Food vs View Image Dataset
+
+## 1. Purpose
+This dataset was created for educational purposes as part of Homework 1 (*Dealing with Data*).  
+It demonstrates how to build, preprocess, augment, and upload an image dataset to Hugging Face.  
+The dataset supports binary image classification tasks and shows how augmentation can expand small collections into larger, balanced sets.
+
+---
+
+## 2. Composition
+- **Domain:** Everyday life photos.  
+- **Samples:** 32 unique, student-created images.  
+- **Classes (binary target):**  
+  - `food` → meals, snacks, and beverages.  
+  - `view` → landscapes, outdoor scenery.  
+- **Split Sizes:**  
+  - Original: 32 images  
+  - Augmented: 352 images  
+
+---
+
+## 3. Collection Process
+- **Source:** All original images were taken by the student using a phone camera.  
+- **Content:** Food photos are close-ups of meals, while view photos capture outdoor landscapes.  
+- **Format:** JPEG/PNG images.  
+- **Resolution:** Resized to 224×224 pixels.  
+- **Ethical Assurance:** No faces, people, or personal identifiers are included.  
+
+---
+
+## 4. Preprocessing & Augmentation
+- **Preprocessing:**  
+  - Resized all images to 224×224.  
+  - Converted to RGB format.  
+- **Augmentation Techniques (label-preserving):**  
+  - Horizontal/vertical flips  
+  - Random rotations (0°, 90°, 180°, 270°)  
+  - Brightness/contrast adjustments  
+  - Random cropping and scaling  
+- **Goal:** Expand dataset to ≥300 samples while preserving labels.  
+
+---
+
+## 5. Labels
+- **Target Variable:** `label`  
+- **Values:**  
+  - `0`: food  
+  - `1`: view  
+
+---
+
+## 6. Splits
+- **Original split:** 32 manually collected images (`original`).  
+- **Augmented split:** 352 synthetic variants via documented augmentation techniques (`augmented`).  
+
+---
+
+## 7. Exploratory Data Analysis (EDA)
+Below are random samples from both classes:
+
+![EDA Contact Sheet](eda_contact_sheet.png)
+
+- **Class counts:** 15 food, 17 view  
+- **Observation:** Food images tend to be close-up shots under artificial lighting, while view images capture natural scenery with broader perspectives.  
+
+---
+
+## 8. Intended Use / Limitations
+- **Use:**  
+  - Educational demo for binary image classification.  
+  - Practice with preprocessing, augmentation, and Hugging Face uploads.  
+- **Limitations:**  
+  - Small dataset; not suitable for real-world production.  
+  - Augmentation does not fully capture real-world variability.  
+
+---
+
+## 9. Ethical Considerations
+- Images are student-owned and contain no personal or sensitive data.  
+- Dataset is safe for academic and research use.  
+
+---
+
+## 10. License
+Released under the **MIT License** for educational and research purposes.  
+
+---
+
+## 11. AI Usage Disclosure
+- **Original images (32):** Taken by the student.  
+- **Augmentation:** Generated via Python libraries (e.g., `torchvision.transforms`).  
+- **Documentation:** Drafted with the assistance of AI tools (ChatGPT) but reviewed and finalized manually.  
+