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# Conflicts:
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* Assert engine precision #6777

* Default to FP32 inputs for TensorRT engines

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* Add missing colon

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TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error

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Move C3 from models.experimental to models.common

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* Add TensorFlow and TFLite Detection

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* Fix reshape dim to support dynamic batching

* Fix reshape dim to support dynamic batching

* Add epsilon argument in tf_BN, which is different between TF and PT

* Set stride to None if not using PyTorch, and do not warmup without PyTorch

* Add list support in check_img_size()

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* sys.path.append('./') to run from yolov5/

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* Export and detect with TensorRT engine file

* Resolve `isort`

* Make validation works with TensorRT engine

* feat: update export docstring

* feat: change suffix from *.trt to *.engine

* feat: get rid of pycuda

* feat: make compatiable with val.py

* feat: support detect with fp16 engine

* Add Lite to Edge TPU string

* Remove *.trt comment

* Revert to standard success logger.info string

* Fix Deprecation Warning

```
export.py:310: DeprecationWarning: Use build_serialized_network instead.
  with builder.build_engine(network, config) as engine, open(f, 'wb') as t:
```

* Revert deprecation warning fix

@imyhxy it seems we can't apply the deprecation warning fix because then export fails, so I'm reverting my previous change here.

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* export onnx to file before building TensorRT engine file

* feat: triger ONNX export failed early

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* New `DetectMultiBackend()` class

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* Fix detect.py URL inference

Allows detect.py to run inference on remote URL sources, i.e.:

```python
!python detect.py --weights yolov5s.pt --source https://ultralytics.com/assets/zidane.jpg  # image URL
!python detect.py --weights yolov5s.pt --source https://ultralytics.com/assets/decelera_landscape.mov  # video URL
```

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* Handle edgetpu model inference

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* Cleanup

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* Clip Objects365 autodownload labels (#5214)

Fixes out of bounds labels that seem to affect ~10% of images in dataset.

* Inplace ops