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26 results

detect.py

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    • Jiacong Fang's avatar
      808bcad3
      Add TensorFlow and TFLite export (#1127) · 808bcad3
      Jiacong Fang authored
      
      * Add models/tf.py for TensorFlow and TFLite export
      
      * Set auto=False for int8 calibration
      
      * Update requirements.txt for TensorFlow and TFLite export
      
      * Read anchors directly from PyTorch weights
      
      * Add --tf-nms to append NMS in TensorFlow SavedModel and GraphDef export
      
      * Remove check_anchor_order, check_file, set_logging from import
      
      * Reformat code and optimize imports
      
      * Autodownload model and check cfg
      
      * update --source path, img-size to 320, single output
      
      * Adjust representative_dataset
      
      * Put representative dataset in tfl_int8 block
      
      * detect.py TF inference
      
      * weights to string
      
      * weights to string
      
      * cleanup tf.py
      
      * Add --dynamic-batch-size
      
      * Add xywh normalization to reduce calibration error
      
      * Update requirements.txt
      
      TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error
      
      * Fix imports
      
      Move C3 from models.experimental to models.common
      
      * Add models/tf.py for TensorFlow and TFLite export
      
      * Set auto=False for int8 calibration
      
      * Update requirements.txt for TensorFlow and TFLite export
      
      * Read anchors directly from PyTorch weights
      
      * Add --tf-nms to append NMS in TensorFlow SavedModel and GraphDef export
      
      * Remove check_anchor_order, check_file, set_logging from import
      
      * Reformat code and optimize imports
      
      * Autodownload model and check cfg
      
      * update --source path, img-size to 320, single output
      
      * Adjust representative_dataset
      
      * detect.py TF inference
      
      * Put representative dataset in tfl_int8 block
      
      * weights to string
      
      * weights to string
      
      * cleanup tf.py
      
      * Add --dynamic-batch-size
      
      * Add xywh normalization to reduce calibration error
      
      * Update requirements.txt
      
      TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error
      
      * Fix imports
      
      Move C3 from models.experimental to models.common
      
      * implement C3() and SiLU()
      
      * 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()
      
      * Add list input support in detect.py
      
      * sys.path.append('./') to run from yolov5/
      
      * Add int8 quantization support for TensorFlow 2.5
      
      * Add get_coco128.sh
      
      * Remove --no-tfl-detect in models/tf.py (Use tf-android-tfl-detect branch for EdgeTPU)
      
      * Update requirements.txt
      
      * Replace torch.load() with attempt_load()
      
      * Update requirements.txt
      
      * Add --tf-raw-resize to set half_pixel_centers=False
      
      * Add --agnostic-nms for TF class-agnostic NMS
      
      * Cleanup after merge
      
      * Cleanup2 after merge
      
      * Cleanup3 after merge
      
      * Add tf.py docstring with credit and usage
      
      * pb saved_model and tflite use only one model in detect.py
      
      * Add use cases in docstring of tf.py
      
      * Remove redundant `stride` definition
      
      * Remove keras direct import
      
      * Fix `check_requirements(('tensorflow>=2.4.1',))`
      
      Co-authored-by: default avatarGlenn Jocher <glenn.jocher@ultralytics.com>
      Add TensorFlow and TFLite export (#1127)
      Jiacong Fang authored
      
      * Add models/tf.py for TensorFlow and TFLite export
      
      * Set auto=False for int8 calibration
      
      * Update requirements.txt for TensorFlow and TFLite export
      
      * Read anchors directly from PyTorch weights
      
      * Add --tf-nms to append NMS in TensorFlow SavedModel and GraphDef export
      
      * Remove check_anchor_order, check_file, set_logging from import
      
      * Reformat code and optimize imports
      
      * Autodownload model and check cfg
      
      * update --source path, img-size to 320, single output
      
      * Adjust representative_dataset
      
      * Put representative dataset in tfl_int8 block
      
      * detect.py TF inference
      
      * weights to string
      
      * weights to string
      
      * cleanup tf.py
      
      * Add --dynamic-batch-size
      
      * Add xywh normalization to reduce calibration error
      
      * Update requirements.txt
      
      TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error
      
      * Fix imports
      
      Move C3 from models.experimental to models.common
      
      * Add models/tf.py for TensorFlow and TFLite export
      
      * Set auto=False for int8 calibration
      
      * Update requirements.txt for TensorFlow and TFLite export
      
      * Read anchors directly from PyTorch weights
      
      * Add --tf-nms to append NMS in TensorFlow SavedModel and GraphDef export
      
      * Remove check_anchor_order, check_file, set_logging from import
      
      * Reformat code and optimize imports
      
      * Autodownload model and check cfg
      
      * update --source path, img-size to 320, single output
      
      * Adjust representative_dataset
      
      * detect.py TF inference
      
      * Put representative dataset in tfl_int8 block
      
      * weights to string
      
      * weights to string
      
      * cleanup tf.py
      
      * Add --dynamic-batch-size
      
      * Add xywh normalization to reduce calibration error
      
      * Update requirements.txt
      
      TensorFlow 2.3.1 -> 2.4.0 to avoid int8 quantization error
      
      * Fix imports
      
      Move C3 from models.experimental to models.common
      
      * implement C3() and SiLU()
      
      * 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()
      
      * Add list input support in detect.py
      
      * sys.path.append('./') to run from yolov5/
      
      * Add int8 quantization support for TensorFlow 2.5
      
      * Add get_coco128.sh
      
      * Remove --no-tfl-detect in models/tf.py (Use tf-android-tfl-detect branch for EdgeTPU)
      
      * Update requirements.txt
      
      * Replace torch.load() with attempt_load()
      
      * Update requirements.txt
      
      * Add --tf-raw-resize to set half_pixel_centers=False
      
      * Add --agnostic-nms for TF class-agnostic NMS
      
      * Cleanup after merge
      
      * Cleanup2 after merge
      
      * Cleanup3 after merge
      
      * Add tf.py docstring with credit and usage
      
      * pb saved_model and tflite use only one model in detect.py
      
      * Add use cases in docstring of tf.py
      
      * Remove redundant `stride` definition
      
      * Remove keras direct import
      
      * Fix `check_requirements(('tensorflow>=2.4.1',))`
      
      Co-authored-by: default avatarGlenn Jocher <glenn.jocher@ultralytics.com>