BinderIQ vs DeckVision

Your trading card collection, organized into digital binders. Scan cards, check for duplicates, research prices, and browse the collection you have built. SCAN AND ORGANIZE Create binders with pages and nine-pocket layouts. Photograph a group of cards or import photos, then review the detected crops before adding them to your collection. Save card details, purchase costs, grades and values in each pocket. CHECK BEFORE YOU BUY Photograph a card to search for possible matches in your collection. Review the match and jump to its binder, page and pocket. Batch Duplicate Check can help you review multiple cards together. IDENTIFY AND RESEARCH AI Card Intelligence helps identify players and characters, years, sets, card numbers and versions. Review and correct the result before saving. Supported cards can show recent completed sales, asking listings and the individual listings behind a result. Availability varies by card, version and market. FIND THE RIGHT VERSION Explore available checklist information for supported products, including parallel names, print runs and pack odds where published. Compare the checklist with the number stamped on your card. A missing checklist or sale is not a zero-dollar value. SPORTS AND TRADING CARD GAMES Organize baseball, football, basketball, hockey, soccer, Formula 1 and entertainment cards, plus supported trading card games including Pokémon, Magic: The Gathering, Yu-Gi-Oh!, Lorcana and One Piece. Pokémon cards can also show TCGplayer market information where available. GRADING LOOKUPS Read supported slab labels and research grading certificates. PSA and Beckett results can include grade, population or sub-grade information where available. Other grading-company links help you continue your research. YOUR DIGITAL BINDER Browse cards in an album with curling pages, or use All Cards to sort and filter your collection. Add a custom binder cover. Photograph both sides of a card to view it in 3D or place it in AR. On iPhone Duo, Album View shows two pages side by side on the wide inner display, and All Cards adapts to the larger screen. EXPORT, SHARE AND SYNC Export your collection to Excel or CSV, with photo options. Share binders with other collectors. Keep your collection on your own devices using iCloud. Free to start, with three AI identifications and storage for up to 100 cards. Optional in-app purchases provide additional collection capacity and AI lookup allowances. Identification, checklist, pricing and grading services require an internet connection. Scanning, OCR, organization and duplicate matching run on your device. Terms of Use: https://binderiq.app/terms Privacy Policy: https://binderiq.app/privacy

DeckVision turns your iPhone into a playing card training data collector. Point the camera at any arrangement of cards, and DeckVision automatically detects and labels each one in real time using on-device machine learning. When detections stabilize, the image is captured automatically -- no tapping required. Every captured image goes into a review queue where you can inspect bounding boxes, correct misidentified cards, and delete false positives before they pollute your dataset. Edits are non-destructive, and you can return to any image at any time. When your dataset is ready, export everything as a single zip file in Create ML object detection format. The archive includes all annotated images, an annotations.json file with bounding boxes and card labels, and a metadata.json file with detection confidence scores and correction history for full provenance tracking. Key features - Real-time card detection with automatic capture when the scene stabilizes - Full annotation review and correction after each scan - Browsable image library with thumbnail grid and detail editing - Create ML-compatible export with annotations and metadata - 100% on-device processing -- no data ever leaves your iPhone - Camera permission managed transparently, revocable at any time DeckVision is built for machine learning practitioners, researchers, and anyone working to improve playing card detection models with real-world, human-verified training data.