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Cleanup Detector labelmap (#4932)
* Add missing labels to default labelmap. Fill any holes with "unknown". Remove unique labelmap for tensorrt. * Replace "truck" with "car" on Openvino labelmap
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@ -91,7 +91,8 @@ RUN wget -qO cpu_model.tflite https://github.com/google-coral/test_data/raw/rele
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COPY labelmap.txt .
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# Copy OpenVino model
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COPY --from=ov-converter /models/public/ssdlite_mobilenet_v2/FP16 openvino-model
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RUN wget -q https://github.com/openvinotoolkit/open_model_zoo/raw/master/data/dataset_classes/coco_91cl_bkgr.txt -O openvino-model/coco_91cl_bkgr.txt
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RUN wget -q https://github.com/openvinotoolkit/open_model_zoo/raw/master/data/dataset_classes/coco_91cl_bkgr.txt -O openvino-model/coco_91cl_bkgr.txt && \
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sed -i 's/truck/car/g' openvino-model/coco_91cl_bkgr.txt
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@ -32,6 +32,3 @@ do
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python3 onnx_to_tensorrt.py -m ${model}
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cp /tensorrt_demos/yolo/${model}.trt ${OUTPUT_FOLDER}/${model}.trt;
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done
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# Download Labelmap
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wget -q https://github.com/openvinotoolkit/open_model_zoo/raw/master/data/dataset_classes/coco_91cl.txt -O ${OUTPUT_FOLDER}/coco_91cl.txt
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@ -228,7 +228,6 @@ detectors:
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model:
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path: /trt-models/yolov7-tiny-416.trt
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labelmap_path: /trt-models/coco_91cl.txt
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input_tensor: nchw
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input_pixel_format: rgb
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width: 416
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@ -706,15 +706,17 @@ def load_labels(path, encoding="utf-8"):
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Dictionary mapping indices to labels.
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"""
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with open(path, "r", encoding=encoding) as f:
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labels = {index: "unknown" for index in range(91)}
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lines = f.readlines()
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if not lines:
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return {}
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if lines[0].split(" ", maxsplit=1)[0].isdigit():
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pairs = [line.split(" ", maxsplit=1) for line in lines]
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return {int(index): label.strip() for index, label in pairs}
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labels.update({int(index): label.strip() for index, label in pairs})
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else:
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return {index: line.strip() for index, line in enumerate(lines)}
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labels.update({index: line.strip() for index, line in enumerate(lines)})
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return labels
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def clean_camera_user_pass(line: str) -> str:
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11
labelmap.txt
11
labelmap.txt
@ -9,6 +9,7 @@
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8 boat
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9 traffic light
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10 fire hydrant
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11 street sign
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12 stop sign
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13 parking meter
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14 bench
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@ -22,8 +23,11 @@
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22 bear
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23 zebra
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24 giraffe
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25 hat
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26 backpack
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27 umbrella
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28 shoe
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29 eye glasses
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30 handbag
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31 tie
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32 suitcase
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@ -38,6 +42,7 @@
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41 surfboard
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42 tennis racket
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43 bottle
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44 plate
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45 wine glass
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46 cup
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47 fork
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@ -58,8 +63,12 @@
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62 couch
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63 potted plant
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64 bed
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65 mirror
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66 dining table
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67 window
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68 desk
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69 toilet
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70 door
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71 tv
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72 laptop
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73 mouse
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@ -71,6 +80,7 @@
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79 toaster
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80 sink
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81 refrigerator
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82 blender
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83 book
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84 clock
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85 vase
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@ -78,3 +88,4 @@
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87 teddy bear
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88 hair drier
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89 toothbrush
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90 hair brush
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