- Re-enable kp.core.set_timeout() which is required for proper device communication
- Fix GUI terminal truncation issue by using append() instead of setPlainText()
- Remove aggressive line limiting that was causing log display to stop midway
- Implement gentler memory management (trim only after 1000+ lines)
- This should resolve pipeline timeout issues and complete log display
The previous USB timeout disable was causing stage timeouts without inference results.
The terminal display issue was due to frequent text replacement causing display corruption.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add StdoutCapture context manager to capture all print() statements
- Connect captured output to GUI terminal display via stdout_captured signal
- Fix logging issue where pipeline initialization and operation logs were not shown in app
- Prevent infinite recursion with _emitting flag in TeeWriter
- Ensure both console and GUI receive all log messages during deployment
- Comment out USB timeout setting that was causing device timeout issues
This resolves the issue where logs would stop showing partially in the app,
ensuring complete visibility of MultiDongle and InferencePipeline operations.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Enable USB timeout (5000ms) for stable communication
- Fix send thread timeout from 0.01s to 1.0s for better blocking
- Update WebcamInferenceRunner to use async pattern (non-blocking)
- Add non-blocking put_input option to prevent frame drops
- Improve thread stopping mechanism with better cleanup
These changes follow Kneron official example pattern and should
enable proper parallel processing across multiple dongles.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Fixed DeviceDescriptorList object attribute error by properly accessing
the device_descriptor_list attribute instead of treating the result as
a direct list of devices.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
This commit integrates the dongle model detection logic into .
It refactors the method to:
- Handle in list or object format.
- Extract and for each device.
- Use to identify dongle models.
- Return a more detailed device information structure.
The previously deleted files were moved to the directory.
- Fix ambiguous truth value error in get_latest_inference_result method
- Fix ambiguous truth value error in postprocess function
- Replace direct array evaluation with explicit length checks
- Use proper None checks instead of truthy evaluation on numpy arrays
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Always store firmware paths (scpu_fw_path, ncpu_fw_path) when provided, not just when upload_fw=True
- Restore firmware upload condition to only run when upload_fw=True
- Fix 'MultiDongle' object has no attribute 'scpu_fw_path' error during pipeline initialization
- Ensure firmware paths are available for both upload and non-upload scenarios
This resolves the pipeline deployment error where firmware paths were missing
even when provided to the constructor, causing initialization failures.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Device Detection Updates:
- Update device series detection to use product_id mapping (0x100 -> KL520, 0x720 -> KL720)
- Handle JSON dict format from kp.core.scan_devices() properly
- Extract usb_port_id correctly from device descriptors
- Support multiple device descriptor formats (dict, list, object)
- Enhanced debug output shows Product ID for verification
Pipeline Deployment Fixes:
- Remove invalid preprocessor/postprocessor parameters from MultiDongle constructor
- Add max_queue_size parameter support to MultiDongle
- Fix pipeline stage initialization to match MultiDongle constructor
- Add auto_detect parameter support for pipeline stages
- Store stage processors as instance variables for future use
Example Updates:
- Update device_detection_example.py to show Product ID in output
- Enhanced error handling and format detection
Resolves pipeline deployment error: "MultiDongle.__init__() got an unexpected keyword argument 'preprocessor'"
Now properly handles real device descriptors with correct product_id to series mapping.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add scan_devices() method using kp.core.scan_devices() for device discovery
- Add connect_auto_detected_devices() for automatic device connection
- Add device series detection (KL520, KL720, KL630, KL730, KL540, etc.)
- Add auto_detect parameter to MultiDongle constructor
- Add get_device_info() and print_device_info() methods to display port IDs and series
- Update connection logic to use kp.core.connect_devices() per official docs
- Add device_detection_example.py with usage examples
- Maintain backward compatibility with manual port specification
Features display dongle series and port ID as requested for better device management.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add DataProcessor abstract base class with process method
- Add PostProcessor class for handling inference output data
- Fix PreProcessor inheritance from DataProcessor
- Resolves "name 'DataProcessor' is not defined" error during pipeline deployment
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
