Update README.md

README.md

@@ -1,5 +1,74 @@
-# audioform_dataset
+---
+license: mit
+task_categories:
+- image-to-text
+- text-to-image
+- audio-classification
+- image-classification
+- tabular-classification
+tags:
+- audio
+- image
+- multimodal
+- visualization
+- audio-visualization
+- 3d-visualization
+- synthetic
+- proof-of-concept
+- frequency-estimation
+- generative-audio
+- music-visualization
+---
+## Audioform_Dataset_v1
 
+This dataset is the very first output from **AUDIOFORM** — a Three.js powered 3D audio visualization tool that turns audio files 
+into beautiful, timestamped visual frames with rich metadata. **AUDIOFORM** by webXOS is available for download in the /audioform/
+folder of this repo so developers can create their own similar datasets. Audio for is a synthetic harmonic oscilator that runs in HTML, 
+think of it as the "Hello World" / MNIST-style dataset application for audio-to-visual multimodal machine learning.
+
+This dataset contains **10 captured frames** from a short uploaded WAV file (played at 1× speed), together with per-frame 
+metadata including dominant frequency, timestamp, and capture info.
+
+## Dataset Structure
+
+```
+audioform_dataset/
+├── images/
+│   ├── frame_0001.png
+│   ├── frame_0002.png
+│   └── ... (10 PNG frames total)
+├── metadata.csv          # Main metadata file (Hugging Face viewer uses this)
+└── README.md
+```
+
+```
+| Column        | Type    | Description                                                                 | Example Value                     |
+|---------------|---------|-----------------------------------------------------------------------------|-----------------------------------|
+| `file_name`   | string  | Relative path to the visualization PNG (required by Hugging Face)           | `images/frame_0001.png`           |
+| `frame_id`    | int     | Sequential frame number (0-based)                                           | 0, 1, 2, …, 9                     |
+| `timestamp`   | float   | Time in seconds when the frame was captured from the audio                  | 5.365, 6.219, 9.504               |
+| `frequency`   | int     | Dominant / main detected audio frequency at capture time (Hz)               | 0 (in this tiny sample)           |
+| `time_scale`  | int     | Playback speed multiplier used during visualization                         | 1                                 |
+| `capture_date`| string  | UTC ISO timestamp when the frame was rendered                               | 2026-01-13T19:57:36.427Z          |
+```
+
+See how fast a tiny diffusion model / GAN / LoRA can memorize & regenerate these exact 10 styles. Use the frames as 
+style references for ControlNet, IP-Adapter, or fine-tuning SD to adopt this neon 3D audio-viz aesthetic.
+
+```
+   This dataset shows the **format** AUDIOFORM produces.  
+   → Feed it real music, voices, field recordings, synths  
+   → Generate 1k–100k+ frames  
+   → Add labels (genre, instrument, mood, multiple freq peaks…)  
+   → Unlock serious applications:
+
+   - Music video auto-generation  
+   - Visual audio classifiers  
+   - Audio-conditioned image/video generation  
+   - Interactive music → 3D art installations  
+   - Novel multimodal music understanding models
+
+```
 ## Dataset Description
 
 This dataset was generated using AUDIOFORM, a 3D audio visualization system.
@@ -29,4 +98,4 @@ This dataset is intended for training machine learning models on audio visualiza
 
 ## Generation Details
 
-Generated with AUDIOFORM v1.0 - A Three.js based audio visualization dataset generator.
+Generated with AUDIOFORM v1.0 - by webXOS