Update README.md
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README.md
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@@ -47,8 +47,6 @@ from PIL import Image
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import matplotlib.pyplot as plt
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import time
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from thop import profile
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from sklearn.metrics import average_precision_score
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import numpy as np
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class SimpleCNN(nn.Module):
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def __init__(self, model_type='f', num_classes=6): # Model tipine göre "model_type" değişkeni "f, c, q" olarak değiştirilebilir.
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@@ -130,13 +128,8 @@ def calculate_performance_metrics(model, device, input_size=(1, 3, 224, 224)):
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avg_v100_b1_time = sum(v100_times_b1) / len(v100_times_b1)
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avg_v100_b32_time = sum(v100_times_b32) / len(v100_times_b32)
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mAP_50_95 = 0
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mAP_50 = 0
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return {
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'size_pixels': 224,
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'mAPval_50_95': mAP_50_95,
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'mAPval_50': mAP_50,
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'speed_cpu_b1': avg_cpu_time,
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'speed_v100_b1': avg_v100_b1_time,
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'speed_v100_b32': avg_v100_b32_time,
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@@ -224,8 +217,6 @@ from PIL import Image
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import matplotlib.pyplot as plt
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import time
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from thop import profile
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from sklearn.metrics import average_precision_score
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import numpy as np
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class SimpleCNN(nn.Module):
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def __init__(self, model_type='f', num_classes=6): # The ‘model_type’ variable can be changed to ‘f, c, q’ according to the model type.
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@@ -307,13 +298,8 @@ def calculate_performance_metrics(model, device, input_size=(1, 3, 224, 224)):
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avg_v100_b1_time = sum(v100_times_b1) / len(v100_times_b1)
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avg_v100_b32_time = sum(v100_times_b32) / len(v100_times_b32)
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mAP_50_95 = 0
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mAP_50 = 0
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return {
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'size_pixels': 224,
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'mAPval_50_95': mAP_50_95,
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'mAPval_50': mAP_50,
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'speed_cpu_b1': avg_cpu_time,
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'speed_v100_b1': avg_v100_b1_time,
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'speed_v100_b32': avg_v100_b32_time,
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import matplotlib.pyplot as plt
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import time
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from thop import profile
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class SimpleCNN(nn.Module):
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def __init__(self, model_type='f', num_classes=6): # Model tipine göre "model_type" değişkeni "f, c, q" olarak değiştirilebilir.
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avg_v100_b1_time = sum(v100_times_b1) / len(v100_times_b1)
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avg_v100_b32_time = sum(v100_times_b32) / len(v100_times_b32)
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return {
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'size_pixels': 224,
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'speed_cpu_b1': avg_cpu_time,
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'speed_v100_b1': avg_v100_b1_time,
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'speed_v100_b32': avg_v100_b32_time,
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import matplotlib.pyplot as plt
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import time
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from thop import profile
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class SimpleCNN(nn.Module):
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def __init__(self, model_type='f', num_classes=6): # The ‘model_type’ variable can be changed to ‘f, c, q’ according to the model type.
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avg_v100_b1_time = sum(v100_times_b1) / len(v100_times_b1)
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avg_v100_b32_time = sum(v100_times_b32) / len(v100_times_b32)
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return {
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'size_pixels': 224,
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'speed_cpu_b1': avg_cpu_time,
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'speed_v100_b1': avg_v100_b1_time,
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'speed_v100_b32': avg_v100_b32_time,
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