Upload README.md

README.md

@@ -0,0 +1,144 @@
+---
+tags:
+  - aerial
+  - temporal
+  - time-series
+  - construction
+  - multiview
+  - change-detection
+  - world-model
+  - urban
+task_categories:
+  - video-classification
+  - image-classification
+  - image-segmentation
+  - object-detection
+size_categories:
+  - small
+license: other
+---
+
+# CityLine — Temporal Aerial Construction Dataset (Sample)
+
+**Temporal Aerial Vision · Construction Progress · Multiview Geometry · San Jose, CA**
+
+CityLine is a multi-year aerial imagery sequence captured from a helicopter during the construction of a major mixed-use development in **San Jose, California**.  
+This sample highlights multiple construction phases over time, with several oblique views per capture date.
+
+The full (commercial) dataset contains **hundreds of high-resolution images** with monthly coverage across several years — suitable for **world models, 3D reconstruction, change detection, construction analytics, and urban growth modeling**.
+
+This dataset is a **limited preview sample** intended for evaluation and experimentation.
+
+---
+
+## 📍 Project Overview
+
+| Property | Value |
+|---------|------|
+| Project name | CityLine |
+| Location | San Jose, California, USA |
+| Capture type | Helicopter-based oblique aerial imagery |
+| Resolution | 12MP JPEG (RAW available commercially) |
+| Coverage period (full set) | 2017 → 2025 (approx.) |
+| Temporal cadence | ~monthly |
+| Viewpoints per capture | Multiple oblique angles |
+| Coordinates | 37.374751, -122.032811 |
+
+---
+
+## 🎯 Machine Learning Use Cases
+
+| Category | Tasks Enabled |
+|---------|---------------|
+| **Temporal Vision** | World models, change detection, temporal consistency |
+| **Multiview Geometry** | Structure-from-motion, NeRF, depth from motion |
+| **Autonomy + Robotics** | Mapping, localization, spatial reasoning |
+| **Construction Analytics** | Progress estimation, digital twins, safety monitoring |
+| **Earth Observation** | Urban growth, infrastructure evolution |
+
+---
+
+## 📁 Dataset Contents (Sample)
+
+Folder structure:
+
+```text
+preview/              # resized JPEG previews for fast HF browsing
+images/               # full-resolution JPEGs grouped by month
+  2017-12/
+  2019-01/
+  2020-06/
+  2021-09/
+  2023-06/
+  2025-01/
+metadata.csv
+```
+
+➡ Preview images are **2048px max dimension**, ideal for Hugging Face’s viewer  
+➡ Full-resolution files contain the highest-quality data for research/licensing
+
+---
+
+### `metadata.csv` Schema
+
+| Column | Description |
+|--------|-------------|
+| `project_id` | Numeric ID for the project |
+| `project_name` | "CityLine" |
+| `filename` | Full-resolution image filename |
+| `preview_filename` | Lower-resolution preview filename |
+| `date` | Capture date parsed from filename |
+| `year_month` | Monthly grouping |
+| `image_seq` | Sequence index derived from filename |
+| `orbit_index` | Orbit grouping (sample = 1) |
+| `orbit_frame` | Ordered view index (1…N) |
+| `latitude` | Project latitude |
+| `longitude` | Project longitude |
+| `notes` | Optional annotation |
+
+---
+
+## 🔧 Quick Usage Example
+
+```python
+import pandas as pd
+from pathlib import Path
+from PIL import Image
+
+meta = pd.read_csv("metadata.csv")
+
+# Load preview image first (fast)
+preview_path = Path("preview") / meta['preview_filename'][0]
+img_preview = Image.open(preview_path).convert("RGB")
+img_preview.show()
+
+# Load matching full-resolution image when needed
+full_path = Path("images") / meta['year_month'][0] / meta['filename'][0]
+img_full = Image.open(full_path).convert("RGB")
+img_full.show()
+```
+
+---
+
+## 🔐 Full Dataset Access & Licensing
+
+This sample is provided for **evaluation purposes only**.
+
+The complete CityLine dataset (836 images) and a library of **270+** full-lifecycle construction projects are available under commercial license:
+
+- Towers
+- Hospitals
+- Stadiums
+- Highways & interchanges
+- Commercial sites
+
+**Contact for full access:**  
+📧 gene@sharpshotsaerial.com
+
+---
+
+## 🛰 About SharpShots Aerial
+
+SharpShots Aerial specializes in long-term helicopter-based imaging of major construction and urban projects, enabling advanced mapping and AI research applications.
+
+---