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basicsr/utils/plot_util.py

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+import re
+
+
+def read_data_from_tensorboard(log_path, tag):
+    """Get raw data (steps and values) from tensorboard events.
+
+    Args:
+        log_path (str): Path to the tensorboard log.
+        tag (str): tag to be read.
+    """
+    from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
+
+    # tensorboard event
+    event_acc = EventAccumulator(log_path)
+    event_acc.Reload()
+    scalar_list = event_acc.Tags()['scalars']
+    print('tag list: ', scalar_list)
+    steps = [int(s.step) for s in event_acc.Scalars(tag)]
+    values = [s.value for s in event_acc.Scalars(tag)]
+    return steps, values
+
+
+def read_data_from_txt_2v(path, pattern, step_one=False):
+    """Read data from txt with 2 returned values (usually [step, value]).
+
+    Args:
+        path (str): path to the txt file.
+        pattern (str): re (regular expression) pattern.
+        step_one (bool): add 1 to steps. Default: False.
+    """
+    with open(path) as f:
+        lines = f.readlines()
+    lines = [line.strip() for line in lines]
+    steps = []
+    values = []
+
+    pattern = re.compile(pattern)
+    for line in lines:
+        match = pattern.match(line)
+        if match:
+            steps.append(int(match.group(1)))
+            values.append(float(match.group(2)))
+    if step_one:
+        steps = [v + 1 for v in steps]
+    return steps, values
+
+
+def read_data_from_txt_1v(path, pattern):
+    """Read data from txt with 1 returned values.
+
+    Args:
+        path (str): path to the txt file.
+        pattern (str): re (regular expression) pattern.
+    """
+    with open(path) as f:
+        lines = f.readlines()
+    lines = [line.strip() for line in lines]
+    data = []
+
+    pattern = re.compile(pattern)
+    for line in lines:
+        match = pattern.match(line)
+        if match:
+            data.append(float(match.group(1)))
+    return data
+
+
+def smooth_data(values, smooth_weight):
+    """ Smooth data using 1st-order IIR low-pass filter (what tensorflow does).
+
+    Reference: https://github.com/tensorflow/tensorboard/blob/f801ebf1f9fbfe2baee1ddd65714d0bccc640fb1/tensorboard/plugins/scalar/vz_line_chart/vz-line-chart.ts#L704  # noqa: E501
+
+    Args:
+        values (list): A list of values to be smoothed.
+        smooth_weight (float): Smooth weight.
+    """
+    values_sm = []
+    last_sm_value = values[0]
+    for value in values:
+        value_sm = last_sm_value * smooth_weight + (1 - smooth_weight) * value
+        values_sm.append(value_sm)
+        last_sm_value = value_sm
+    return values_sm