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import os |
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import streamlit as st |
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import glob |
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import pandas as pd |
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import matplotlib.pyplot as plt |
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def run_eda(): |
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st.title('CNN Image Classifier') |
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train_dir = "Data/train" |
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for files in os.listdir(train_dir): |
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print(os.path.join(train_dir,files)) |
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num_A = len(glob.glob(os.path.join(train_dir, "normal", "*.png"))) |
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num_ad = len(glob.glob(os.path.join(train_dir, "adenocarcinoma_left.lower.lobe_T2_N0_M0_Ib", "*.png"))) |
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num_sq = len(glob.glob(os.path.join(train_dir, "squamous.cell.carcinoma_left.hilum_T1_N2_M0_IIIa", "*.png"))) |
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num_lg = len(glob.glob(os.path.join(train_dir, "large.cell.carcinoma_left.hilum_T2_N2_M0_IIIa", "*.png"))) |
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class_names = ['Normal', 'Adenocarcinoma', 'Squamous', 'Large Cell'] |
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num_images = [num_A, num_ad, num_sq, num_lg] |
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fig, ax = plt.subplots() |
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ax.bar(class_names, num_images) |
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ax.set_title('Banyaknya Data Setiap Kelas pada Dataset Train') |
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ax.set_xlabel('Kelas') |
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ax.set_ylabel('Jumlah Data') |
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st.pyplot(fig) |