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+# 🖼️ AI Visual Matching & Product Resolution Sample Dataset
+
+This dataset is a sample corpus designed to train computer vision models, multimodal LLMs, and e-commerce AI agents on **Visual Matching and Product Resolution** tasks. 
+
+**This clean, structured sample was extracted and normalized by the [Octoparse Managed Data Service](https://www.octoparse.com/data-service/web-data-for-ai) team.**
+
+## 📊 Dataset Overview
+Training models to match identical products across different websites requires high-quality image-to-text and image-to-image pairs. Building the pipeline to extract these images, bypass anti-bot protections, and structure the metadata takes months of engineering. 
+
+We’ve provided a sample of what a production-ready visual matching pipeline looks like.
+
+* **Format:** JSONL / Parquet (Replace with your actual format)
+* **Domain:** E-commerce / Retail 
+* **Use Cases:** Multimodal fine-tuning, automated catalog matching, visual search training.
+
+## 🗂️ Data Structure (Schema)
+*(Note: 替换成你真实的字段)*
+* `image_url`: High-resolution source image link
+* `product_title`: Extracted product name
+* `source_platform`: Website where the data was extracted
+* `matched_id`: Unique identifier for identical products across platforms
+* `metadata`: JSON object containing variants, colors, and dimensions
+
+## 🚀 Need 10 Million Rows of Custom Training Data?
+Common Crawl is too noisy. Building your own scrapers is a waste of your engineering talent.
+
+If your team is building an AI agent or fine-tuning an LLM and needs highly specific, deduplicated data (text, images, or social signals from platforms like Xiaohongshu/Douyin):
+
+**Stop building scrapers. Let us build the pipeline.**
+
+👉 **[Request a Free Custom Sample Dataset from Octoparse](https://www.octoparse.com/data-service/web-data-for-ai)**
+*We scope the project, handle the extraction, and deliver analysis-ready data to your S3/Snowflake in days.*