Tochukwu Nwoke Tob-iee
Tob-iee
/ gist:ec4a68a89b093e0d00e155292e585695
Last active
September 21, 2020 08:07
optimize models
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| #Optimize the safety model | |
| python3 /opt/intel/openvino/deployment_tools/tools/model_optimizer/mo_caffe.py --input_model <path to caffemodel file> --input_proto <path to prototxt file> -o <specify the output directory> | |
| #Optimize the mask model | |
| python3 /opt/intel/openvino/deployment_tools/tools/model_optimizer/mo_caffe.py --input_model <path to caffemodel file> --input_proto <path to prototxt file> -o <specify the output directory> |
Tob-iee
/ gist:4ef845f60651cda66e1d8fb858604ed8
Last active
September 21, 2020 08:07
download models from OpenVINO's model directory
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| #Navigate to the model downloader directory and download the models | |
| #Download the person detection model | |
| python3 /opt/intel/openvino/deployment_tools/tools/model_downloader/downloader.py --name "person-detection-retail-0013" | |
| #Download the face detection model | |
| python /opt/intel/openvino/deployment_tools/tools/model_downloader/downloader.py --name "face-detection-adas-binary-0001" | |
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| #include "tensorflow/lite/micro/examples/micro_speech/main_functions.h" | |
| #include "tensorflow/lite/micro/examples/micro_speech/audio_provider.h" | |
| #include "tensorflow/lite/micro/examples/micro_speech/command_responder.h" | |
| #include "tensorflow/lite/micro/examples/micro_speech/feature_provider.h" | |
| #include "tensorflow/lite/micro/examples/micro_speech/micro_features/micro_model_settings.h" | |
| #include "tensorflow/lite/micro/examples/micro_speech/micro_features/model.h" | |
| #include "tensorflow/lite/micro/examples/micro_speech/recognize_commands.h" | |
| #include "tensorflow/lite/micro/kernels/micro_ops.h" | |
| #include "tensorflow/lite/micro/micro_error_reporter.h" |
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| #include "tensorflow/lite/micro/examples/micro_speech/micro_features/micro_model_settings.h" | |
| const char* kCategoryLabels[kCategoryCount] = { | |
| "silence", | |
| "unknown", | |
| "yes", | |
| "no", | |
| }; |
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| #include "tensorflow/lite/micro/examples/micro_speech/micro_features/model.h" | |
| // We need to keep the data array aligned on some architectures. | |
| #ifdef __has_attribute | |
| #define HAVE_ATTRIBUTE(x) __has_attribute(x) | |
| #else | |
| #define HAVE_ATTRIBUTE(x) 0 | |
| #endif | |
| #if HAVE_ATTRIBUTE(aligned) || (defined(__GNUC__) && !defined(__clang__)) | |
| #define DATA_ALIGN_ATTRIBUTE __attribute__((aligned(4))) |
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| stages: | |
| ELT: | |
| cmd: python src/data_preprocessor.py -s train test valid -o "./data_store/data/American | |
| Sign Language Letters.v1-v1.tfrecord" | |
| deps: | |
| - src/data_preprocessor.py | |
| outs: | |
| - ./data_store/data/American Sign Language Letters.v1-v1.tfrecord | |
| feature_tranform-train: | |
| cmd: python src/train.py -dt True |
Tob-iee
/ get_labels.py
Created
September 13, 2023 13:56
Get the label names for the training dataset version from its label objects.
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| labels = train_dataset_version.list_labels() | |
| label_names = [label.name for label in labels] |
Tob-iee
/ coco_format_loader.py
Created
September 13, 2023 14:00
Built, write and read annotations in COCO format using the COCO library
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| def coco_format_loader(train_dataset_version, label_names, coco_annotations_path): | |
| coco_annotation = train_dataset_version.build_coco_file_locally( | |
| enforced_ordered_categories=label_names | |
| ) | |
| annotations_dict = coco_annotation.dict() | |
| with open(coco_annotations_path, "w") as f: | |
| f.write(json.dumps(annotations_dict)) | |
| annotations_coco = COCO(coco_annotations_path) | |
| return annotations_coco |
Tob-iee
/ label_map.py
Created
September 13, 2023 14:01
Create a label map of the labels and their respective “ids” from the COCO annotation categories.
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| cats = annotations_coco.cats | |
| id2label = {str(k): v['name'] for k,v in cats.items()} | |
| label2id = {v: k for k, v in id2label.items()} |
Tob-iee
/ label_map_log.py
Created
September 13, 2023 14:03
Log the label maps to your Picsellia experiment.
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| # log dataset labels to the picsellia experiment | |
| experiment.log("labelmap", id2label, type= LogType.TABLE, replace=True) |
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