| --- |
| task_categories: |
| - text-to-image |
| language: |
| - en |
| tags: |
| - text-to-image |
| - diffusion |
| - image-caption |
| - imagefolder |
| - rectified-flow |
| - echo-vision |
| license: apache-2.0 |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # EchoVision-45K |
|
|
| **Training data for [Echo-Vision-1](https://huggingface.co/Maxilicious20/echo-vision-1)** — a two-stage coarse-to-fine rectified-flow text-to-image model trained from scratch on a single consumer GPU. |
|
|
| > ~45,000 image–caption pairs · max 768 px · machine-generated captions · copyright-filtered · compressed JPEG |
|
|
| --- |
|
|
| ## Dataset Summary |
|
|
| EchoVision-45K is the curated dataset used to train **Echo-Vision-1**, a cascade latent-diffusion model (draft 384 px → final 768 px). It consists of square-cropped web images paired with detailed machine-generated captions. |
|
|
| - **Images:** max side 768 px, optimized JPEG (quality 85). Larger originals were downscaled because the model never consumes more than 768 px. |
| - **Captions:** generated by **Florence-2-large** (`<MORE_DETAILED_CAPTION>`), with ~7 k high-quality single-sentence captions from **Qwen2-VL-2B-Instruct** and BLIP fallbacks. |
| - **Safety:** a two-layer copyright filter (deterministic franchise/brand/watermark text blacklist + CLIP zero-shot visual flagging) removed logos, watermarks, and licensed-franchise content. |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("Maxilicious20/echo-vision-45k") |
| sample = ds["train"][0] |
| sample["image"] # PIL.Image (<=768px) |
| sample["caption"] # str |
| ``` |
|
|
| Training-style transform: |
|
|
| ```python |
| from torchvision import transforms |
| tf = transforms.Compose([ |
| transforms.Resize((768, 768)), |
| transforms.ToTensor(), |
| transforms.Normalize([0.5], [0.5]), |
| ]) |
| x = tf(sample["image"]) # -> [3,768,768] in [-1,1] |
| ``` |
|
|
| ## Dataset Structure |
|
|
| - **Config:** `imagefolder` (auto-detected) |
| - **Features:** `image` (Image), `caption` (string) |
| - **Split:** `train` (~45 k examples; exact count in the Files/Viewer) |
|
|
| ## Data Collection & Processing |
|
|
| 1. **Collection:** web images downloaded with associated queries. |
| 2. **Captioning:** Florence-2-large / Qwen2-VL-2B / BLIP. |
| 3. **Filtering:** resolution & sharpness (Laplacian) pre-filter. |
| 4. **Copyright removal:** text blacklist (franchises, brands, "watermark", "fan art", ©/™/® …) + CLIP zero-shot visual flagging → flagged pairs deleted. |
| 5. **Compression:** downscale to ≤768 px + JPEG q85 (no training-relevant information lost). |
|
|
| ## Limitations & Biases |
|
|
| - Web-scraped imagery inherits the **biases of the open web** (demographic, cultural, aesthetic). |
| - Machine captions can be **noisy or incomplete**. |
| - Despite filtering, residual copyrighted or identifiable content may remain; this dataset is intended for **research only**. |
|
|
| ## License & Third-Party Content |
|
|
| The dataset's original contributions — captions, metadata, curation/filtering code, and the |
| compiled arrangement — are released under the **Apache License 2.0**. |
|
|
| The underlying images were collected from public web sources and **remain the property of |
| their respective copyright holders**. The Apache-2.0 license does **not** grant rights to |
| these third-party images. This dataset is provided for **research only**. |
|
|
| If you hold rights to any image and wish it removed, please open a discussion — it will be |
| taken down promptly. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{echovision45k, |
| title = {EchoVision-45K: A Copyright-Filtered Image--Caption Dataset |
| for Text-to-Image Diffusion Research}, |
| author = {<Your Name>}, |
| year = {2026}, |
| howpublished = {\url{https://huggingface.co/datasets/Maxilicious20/echo-vision-45k}} |
| } |
| ``` |
|
|
| --- |
|
|
| *Companion model: [Echo-Vision-1](https://huggingface.co/Maxilicious20/echo-vision-1) (Apache-2.0) · Built on a single RTX 4060.* |
