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CrossPascal EA020
Pre-release
EA020 r7 keeps the setup and file-inventory corrections from r6 and uses a separate installation directory, so an earlier SDK receipt cannot block the revised download. Existing installations are preserved. The Pascal code, projects and binaries are unchanged from r5.
EA020 r6 corrects YOLO setup links when switching between detection and classification, clarifies Gemma device choices and native image decoding, and supplies SDK component indexes that match the shipped files. The Pascal code, projects and binaries are unchanged from r5.
Current downloads
The automatic GitHub Source code ZIP and tar.gz capture the original EA020 tag. Earlier SDK and source attachments remain available for installations pinned to their checksums.
EA020 r5 corrects the PaddleOCR image dimensions in Delphi and places each path field before Browse in the keyboard order. The vision download guide now matches the published setup sizes. The revised PaddleOCR example was built and checked in Delphi 13.2 and Lazarus 4.8; CPU and CUDA sm_89 runs passed.
Current release inventory | Current Prepare manifest
CrossPascal EA020 adds PaddleOCR to the native Windows x64 SDK. The Delphi and Lazarus example finds text regions in a photo, reads each crop, and saves UTF-8 text or JSON with region coordinates and confidence scores.
Prepare and run
- Prepare PaddleOCR for CPU for Windows x64 with AVX2 and FMA.
- Prepare PaddleOCR for NVIDIA GPU with a CUDA 12.8 driver and at least 2 GiB of free GPU memory.
- All example launchers and the revised Windows x64 SDK.
Extract the ZIP, open its folder and run Prepare.cmd. The CPU and GPU folders are prepare-paddleocr-cpu and prepare-paddleocr-gpu. The prepared example opens the sample photo and points to the two model folders. Select Read text. The same source builds with Delphi 13.2 and Lazarus 4.8. The supplied example executable is a Lazarus build.
The revised launchers wait for a key after showing the setup result, including the Delphi and Lazarus project paths or an error. The revised SDK installs alongside the original EA020 SDK and uses the shared download cache for model bundles and dependencies. For scripted runs set CROSSPASCAL_PREPARE_NO_PAUSE=1.
CPU and CUDA example launchers
Use the device-specific launcher to prepare the same Pascal project on CPU or CUDA. The combined launcher includes all 14 projects and supports automatic device selection.
| Example | CPU | NVIDIA CUDA |
|---|---|---|
| QwenChat | Prepare CPU | Prepare CUDA |
| GemmaChat | Prepare CPU | Prepare CUDA |
| LoadUnload | Prepare CPU | Prepare CUDA |
| GenerateText | Prepare CPU | Prepare CUDA |
| GenerationSettings | Prepare CPU | Prepare CUDA |
| StreamAndStop | Prepare CPU | Prepare CUDA |
| RepeatedRequests | Prepare CPU | Prepare CUDA |
| ImagePrompt | Prepare CPU | Prepare CUDA |
Model downloads
The download catalog lists the separate PP-OCRv5 Server detector and recognizer archives, SHA-256 checksums for the downloaded ZIPs and the DLLs inside them, and the pinned ONNX source archives. The legacy sha256 field still identifies the DLL. Use archive_sha256 to check a downloaded model ZIP. CPU and CUDA packages are separate. The CUDA targets are compute capabilities 6.1, 7.5, 8.6, 8.9 and 12.0. Extract the matching detector and recognizer ZIPs into the same parent to obtain the det and rec model folders. Keep the dictionary with the recognizer.
CrossPascal Converter can compile the pinned ONNX exports into native TVM bundles. The recognizer export needs ppocrv5_dict.txt beside model.onnx. Inference and conversion run without Python. The example guide has the setup steps and model terms.
Verification and scope
The fixed 960 × 960 detection and 48 × 320 recognition profiles were compared with the original ONNX path on two photos. The native CPU and sm_89 CUDA runs matched the reference text in 43 regions per device, with region corners within one pixel and confidence within 0.01. The other CUDA targets have compiled and checked kernel images. Wide text crops are constrained by the recognizer width.
PaddlePaddle publishes PP-OCRv5 Server under Apache-2.0. The model archives retain the license, provenance and modification notice. Clipper 6.4.2 uses the Boost Software License, and original CrossPascal code uses MIT. The source archive includes the corresponding Pascal and Clipper sources.