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need a feature that can draw line plots from log files to reflect how the model behaves on the validation set during training
The text was updated successfully, but these errors were encountered:
this may help
import os import re import matplotlib.pyplot as plt import mplcursors def extract_float_numbers(line): """ Extracts a floating-point number from the line containing the first floating-point number after "AP: ". """ match = re.search(r'AP: (\d+\.\d+)', line) if match: return float(match.group(1)) else: return None def read_log_file(file_path): """ Read log files and extract floating-point numbers. """ float_numbers = [] with open(file_path, 'r') as file: for line in file: if "Epoch(val)" in line: number = extract_float_numbers(line) if number is not None: float_numbers.append(number) return float_numbers def plot_line_chart(float_numbers): """ Draw a line chart. """ _, ax = plt.subplots() ax.plot(range(len(float_numbers)), float_numbers) ax.set(xlabel='Index', ylabel='Value', title='Line Chart') ax.set_xlim(0, 25) ax.set_ylim(0.4, 0.75) # Labeled data point for i, value in enumerate(float_numbers): ax.annotate(f'{value:.2f}', (i, value), textcoords="offset points", xytext=(0,10), ha='center', fontsize=2) # Add interactive tags colorss = ['g', 'r', 'c', 'm', 'y', 'k', 'b'] offs = -20 def main(): # Obtain the.log file in the current directory log_files = [f for f in os.listdir() if f.endswith('.log')] _, ax = plt.subplots() ax.set(xlabel='epoch/10', ylabel='AP', title='Line Chart') ax.set_xlim(0, 25) ax.set_ylim(0.5, 0.75) for j, pa in enumerate(log_files): log_file_path = pa float_numbers = read_log_file(log_file_path) ax.plot(range(len(float_numbers)), float_numbers, color=colorss[j % len(colorss)]) for i, value in enumerate(float_numbers): ax.annotate(f'{value:.3f}', (i, value), textcoords="offset points", xytext=(0, offs + 40 * j), ha='center') mplcursors.cursor(hover=True) plt.show() if __name__ == "__main__": main()
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need a feature that can draw line plots from log files to reflect how the model behaves on the validation set during training
The text was updated successfully, but these errors were encountered: