High-Volume Data Collection AI-Powered Sports and Coin Grading Machine Learning Database
Budget: $750 – $1,500 USD
Project Title: High-Volume Data Collection for AI-Powered Sports Card & Coin Grading
**Budget:** $700–$1,200 (negotiable based on volume)
**Duration:** 2–3 weeks
**Project Overview:**
We are building a cutting-edge vision LLM to become the world’s most accurate automated grader for sports cards and coins. To achieve this, we need a large, diverse dataset of high-quality photos showing both the front and back of graded sports cards (e.g., PSA, BGS) and graded coins (e.g., PCGS). Your role will be to source, organize, and deliver these images to train our AI models.
**Key Requirements:**
1. **Image Specifications:**
- Minimum 10,000 unique graded sports cards (baseball, basketball, football, hockey, and Pokemon) to each numerical grade and 7,000 unique numerically graded coins.
- Each card/coin must have clear, well-lit photos of **both front and back**.
- Include variety in conditions (any brand e.g., PSA 1–10, BGS 1-10 ect.) and grading companies.
- Photos should mimic real-world conditions, and be in Hi-Resolution JPG format (e.g., smartphone shots, slight angles) to improve model robustness.
- Images with any glare must be rejected
-Graded autographed cards to be rejected
2. **Data Organization:**
- Label images with: card/coin name, year, grading company, grade, and notable flaws (e.g., corner wear, centering issues).
- Organize into folders by sport/card type or coin denomination.
3. **Source Methods:**
- Use public databases (e.g., eBay, TCGPlayer, PCGS) or collector communities.
- Ensure no copyrighted watermarks or third-party branding (e.g., avoid PSA slab logos unless necessary).
4. **Deliverables:**
- ZIP file with all images and a CSV/Excel metadata sheet.
-Images in JPG format
-Images must show card in the plastic slabs with grading label front and back.
**Skills Needed:**
- Experience in data collection, web scraping, or access to collectible databases.
- Attention to detail (e.g., verifying grades, avoiding duplicates).
- Familiarity with sports cards/coins is a plus but not required.
- Very low amounts of duplicates (under5%)
**Budget Notes:**
- Higher budgets available for exceptional quality or larger datasets.
- Long-term collaboration possible for ongoing model improvements.
Let’s build the future of collectibles grading together!
**Budget:** $700–$1,200 (negotiable based on volume)
**Duration:** 2–3 weeks
**Project Overview:**
We are building a cutting-edge vision LLM to become the world’s most accurate automated grader for sports cards and coins. To achieve this, we need a large, diverse dataset of high-quality photos showing both the front and back of graded sports cards (e.g., PSA, BGS) and graded coins (e.g., PCGS). Your role will be to source, organize, and deliver these images to train our AI models.
**Key Requirements:**
1. **Image Specifications:**
- Minimum 10,000 unique graded sports cards (baseball, basketball, football, hockey, and Pokemon) to each numerical grade and 7,000 unique numerically graded coins.
- Each card/coin must have clear, well-lit photos of **both front and back**.
- Include variety in conditions (any brand e.g., PSA 1–10, BGS 1-10 ect.) and grading companies.
- Photos should mimic real-world conditions, and be in Hi-Resolution JPG format (e.g., smartphone shots, slight angles) to improve model robustness.
- Images with any glare must be rejected
-Graded autographed cards to be rejected
2. **Data Organization:**
- Label images with: card/coin name, year, grading company, grade, and notable flaws (e.g., corner wear, centering issues).
- Organize into folders by sport/card type or coin denomination.
3. **Source Methods:**
- Use public databases (e.g., eBay, TCGPlayer, PCGS) or collector communities.
- Ensure no copyrighted watermarks or third-party branding (e.g., avoid PSA slab logos unless necessary).
4. **Deliverables:**
- ZIP file with all images and a CSV/Excel metadata sheet.
-Images in JPG format
-Images must show card in the plastic slabs with grading label front and back.
**Skills Needed:**
- Experience in data collection, web scraping, or access to collectible databases.
- Attention to detail (e.g., verifying grades, avoiding duplicates).
- Familiarity with sports cards/coins is a plus but not required.
- Very low amounts of duplicates (under5%)
**Budget Notes:**
- Higher budgets available for exceptional quality or larger datasets.
- Long-term collaboration possible for ongoing model improvements.
Let’s build the future of collectibles grading together!
Related categories:
Photoshop
Web Scraping
Illustration
Data Mining
Image Processing
Data Collection
Data Management
AI Development