Lucas Oskorep
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
import pandas as pd
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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df = pd.read_csv("sub1_non_transfer.csv")
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df2 = pd.read_csv("poke_evos.csv")
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evos = []
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for index, row in df2.iterrows():
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print(row)
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s = ""
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s+=row["stage1"] if not pd.isnull(row["stage1"]) else ""
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s+=row["stage2"] if not pd.isnull(row["stage2"]) else ""
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s+=row["stage3"] if not pd.isnull(row["stage3"]) else ""
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evos.append(s.lower().replace(" ", "-").rstrip())
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incorrect = df[df["prediction"]!= df["true_val"]]
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total_same_fam = 0
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for index, row in incorrect.iterrows():
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img = mpimg.imread("./SingleImageTestSet/" + row['fname'])
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imgplot = plt.imshow(img)
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title = f"Predicted - {row['prediction']}, Actual - {row['true_val']}"
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for evo in evos:
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if row['prediction'] in evo and row['true_val'] in evo:
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title+=f"\n same family name detected - {evo}"
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total_same_fam+=1
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plt.title(title)
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plt.show()
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print(f"The total number of incorrect entries from same families is {total_same_fam} - {total_same_fam/len(incorrect)}") |