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https://github.com/clearml/clearml
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63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
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# ClearML - Example of manual model reporting
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from clearml import Task, OutputModel
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from clearml.utilities.plotly_reporter import SeriesInfo
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import pandas as pd
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import numpy as np
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# Connecting ClearML with the current process,
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task = Task.init(project_name="examples", task_name="Model reporting plots example")
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# Create output model and connect it to the task
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output_model = OutputModel(task=task)
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# Optional: add labels to the model, so we do not forget
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labels = {"background": 0, "cat": 1, "dog": 2}
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output_model.update_labels(labels)
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# Register an already existing Model file somewhere
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model_url = "https://github.com/ultralytics/yolov5/releases/download/v6.2/yolov5x6.pt"
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output_model.update_weights(register_uri=model_url)
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output_model.report_scalar("Reported Metrics", "Val - mAP@50", 72.7, 0)
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output_model.report_single_value("Total epochs", 8)
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df = pd.DataFrame(
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{
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"Model": ["YOLOv5n", "YOLOv5s", "YOLOv5m6", "YOLOv5x6"],
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"size (pixels)": [640, 640, 1280, 1280],
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"Val - mAP@50-95": [28.0, 37.4, 51.3, 55.0],
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"CPU Speed b1 (ms)": [45, 98, 887, 3136],
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}
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)
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output_model.report_table(
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title="Summary Table", series="Comparison", iteration=0, table_plot=df
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)
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output_model.report_line_plot(
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title="Accuracy",
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series=[
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SeriesInfo(
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name="Validation",
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data=np.array(
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[
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[0, 0.3],
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[1, 0.55],
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[2, 0.7],
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[3, 0.77],
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[4, 0.8],
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[5, 0.816],
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[6, 0.822],
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[7, 0.829],
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]
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),
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)
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],
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xaxis="Iteration",
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yaxis="Validation Accuracy",
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)
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# Or upload a local model file to be later used
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# output_model.update_weights(weights_filename="/path/to/file.onnx")
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print("Model registration completed")
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