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Miscellaneous Fixes (#20841)
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* show id field when editing zone * improve zone capitalization * Update NPU models and docs * fix mobilepage in tracked object details * Use thread lock for openvino to avoid concurrent requests with JinaV2 * fix hashing function to avoid collisions * remove extra flex div causing overflow * ensure header stays on top of video controls * don't smart capitalize friendly names * Fix incorrect object classification crop * don't display submit to plus if object doesn't have a snapshot * check for snapshot and clip in actions menu * frigate plus submission fix still show frigate+ section if snapshot has already been submitted and run optimistic update, local state was being overridden * Don't fail to show 0% when showing classification * Don't fail on file system error * Improve title and description for review genai * fix overflowing truncated review item description in detail stream * catch events with review items that start after the first timeline entry review items may start later than events within them, so subtract a padding from the start time in the filter so the start of events are not incorrectly filtered out of the list in the detail stream * also pad on review end_time * fix * change order of timeline zoom buttons on mobile * use grid to ensure genai title does not cause overflow * small tweaks * Cleanup --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
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Nicolas Mowen
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@@ -261,6 +261,8 @@ OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. It will al
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:::tip
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**NPU + GPU Systems:** If you have both NPU and GPU available (Intel Core Ultra processors), use NPU for object detection and GPU for enrichments (semantic search, face recognition, etc.) for best performance and compatibility.
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When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be:
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```yaml
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@@ -283,7 +285,7 @@ detectors:
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| [RF-DETR](#rf-detr) | ✅ | ✅ | Requires XE iGPU or Arc |
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| [YOLO-NAS](#yolo-nas) | ✅ | ✅ | |
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| [MobileNet v2](#ssdlite-mobilenet-v2) | ✅ | ✅ | Fast and lightweight model, less accurate than larger models |
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| [YOLOX](#yolox) | ✅ | ? | |
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| [YOLOX](#yolox) | ✅ | ? | |
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| [D-FINE](#d-fine) | ❌ | ❌ | |
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#### SSDLite MobileNet v2
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