From 45838ec080a416aff8f8a9d4ba900c8eb8d9ee6c Mon Sep 17 00:00:00 2001
From: Alex Burlacu <alex.burlacu@clear.ml>
Date: Thu, 23 Mar 2023 19:08:40 +0200
Subject: [PATCH] Add an example of model with plots

---
 examples/reporting/model_reporting_plots.py | 62 +++++++++++++++++++++
 1 file changed, 62 insertions(+)
 create mode 100644 examples/reporting/model_reporting_plots.py

diff --git a/examples/reporting/model_reporting_plots.py b/examples/reporting/model_reporting_plots.py
new file mode 100644
index 00000000..ecba52a1
--- /dev/null
+++ b/examples/reporting/model_reporting_plots.py
@@ -0,0 +1,62 @@
+# ClearML - Example of manual model reporting
+from clearml import Task, OutputModel
+from clearml.utilities.plotly_reporter import SeriesInfo
+import pandas as pd
+import numpy as np
+
+# Connecting ClearML with the current process,
+task = Task.init(project_name="examples", task_name="Model reporting plots example")
+
+# Create output model and connect it to the task
+output_model = OutputModel(task=task)
+
+# Optional: add labels to the model, so we do not forget
+labels = {"background": 0, "cat": 1, "dog": 2}
+output_model.update_labels(labels)
+
+# Register an already existing Model file somewhere
+model_url = "https://github.com/ultralytics/yolov5/releases/download/v6.2/yolov5x6.pt"
+output_model.update_weights(register_uri=model_url)
+
+output_model.report_scalar("Reported Metrics", "Val - mAP@50", 72.7, 0)
+output_model.report_single_value("Total epochs", 8)
+
+df = pd.DataFrame(
+    {
+        "Model": ["YOLOv5n", "YOLOv5s", "YOLOv5m6", "YOLOv5x6"],
+        "size (pixels)": [640, 640, 1280, 1280],
+        "Val - mAP@50-95": [28.0, 37.4, 51.3, 55.0],
+        "CPU Speed b1 (ms)": [45, 98, 887, 3136],
+    }
+)
+output_model.report_table(
+    title="Summary Table", series="Comparison", iteration=0, table_plot=df
+)
+
+output_model.report_line_plot(
+    title="Accuracy",
+    series=[
+        SeriesInfo(
+            name="Validation",
+            data=np.array(
+                [
+                    [0, 0.3],
+                    [1, 0.55],
+                    [2, 0.7],
+                    [3, 0.77],
+                    [4, 0.8],
+                    [5, 0.816],
+                    [6, 0.822],
+                    [7, 0.829],
+                ]
+            ),
+        )
+    ],
+    xaxis="Iteration",
+    yaxis="Validation Accuracy",
+)
+
+# Or upload a local model file to be later used
+# output_model.update_weights(weights_filename="/path/to/file.onnx")
+
+print("Model registration completed")