Upload 2 files

CNN.py

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+import pandas as pd
+import torch.nn as nn
+
+class CNN(nn.Module):
+    def __init__(self, K):
+        super(CNN, self).__init__()
+        self.conv_layers = nn.Sequential(
+            # conv1
+            nn.Conv2d(in_channels=3, out_channels=32,
+                      kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.BatchNorm2d(32),
+            nn.Conv2d(in_channels=32, out_channels=32,
+                      kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.BatchNorm2d(32),
+            nn.MaxPool2d(2),
+            # conv2
+            nn.Conv2d(in_channels=32, out_channels=64,
+                      kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.BatchNorm2d(64),
+            nn.Conv2d(in_channels=64, out_channels=64,
+                      kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.BatchNorm2d(64),
+            nn.MaxPool2d(2),
+            # conv3
+            nn.Conv2d(in_channels=64, out_channels=128,
+                      kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.BatchNorm2d(128),
+            nn.Conv2d(in_channels=128, out_channels=128,
+                      kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.BatchNorm2d(128),
+            nn.MaxPool2d(2),
+            # conv4
+            nn.Conv2d(in_channels=128, out_channels=256,
+                      kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.BatchNorm2d(256),
+            nn.Conv2d(in_channels=256, out_channels=256,
+                      kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.BatchNorm2d(256),
+            nn.MaxPool2d(2),
+        )
+
+        self.dense_layers = nn.Sequential(
+            nn.Dropout(0.4),
+            nn.Linear(50176, 1024),
+            nn.ReLU(),
+            nn.Dropout(0.4),
+            nn.Linear(1024, K),
+        )
+
+    def forward(self, X):
+        out = self.conv_layers(X)
+
+        # Flatten
+        out = out.view(-1, 50176)
+
+        # Fully connected
+        out = self.dense_layers(out)
+
+        return out
+
+
+idx_to_classes = {0: 'Apple___Apple_scab',
+                  1: 'Apple___Black_rot',
+                  2: 'Apple___Cedar_apple_rust',
+                  3: 'Apple___healthy',
+                  4: 'Background_without_leaves',
+                  5: 'Blueberry___healthy',
+                  6: 'Cherry___Powdery_mildew',
+                  7: 'Cherry___healthy',
+                  8: 'Corn___Cercospora_leaf_spot Gray_leaf_spot',
+                  9: 'Corn___Common_rust',
+                  10: 'Corn___Northern_Leaf_Blight',
+                  11: 'Corn___healthy',
+                  12: 'Grape___Black_rot',
+                  13: 'Grape___Esca_(Black_Measles)',
+                  14: 'Grape___Leaf_blight_(Isariopsis_Leaf_Spot)',
+                  15: 'Grape___healthy',
+                  16: 'Orange___Haunglongbing_(Citrus_greening)',
+                  17: 'Peach___Bacterial_spot',
+                  18: 'Peach___healthy',
+                  19: 'Pepper,_bell___Bacterial_spot',
+                  20: 'Pepper,_bell___healthy',
+                  21: 'Potato___Early_blight',
+                  22: 'Potato___Late_blight',
+                  23: 'Potato___healthy',
+                  24: 'Raspberry___healthy',
+                  25: 'Soybean___healthy',
+                  26: 'Squash___Powdery_mildew',
+                  27: 'Strawberry___Leaf_scorch',
+                  28: 'Strawberry___healthy',
+                  29: 'Tomato___Bacterial_spot',
+                  30: 'Tomato___Early_blight',
+                  31: 'Tomato___Late_blight',
+                  32: 'Tomato___Leaf_Mold',
+                  33: 'Tomato___Septoria_leaf_spot',
+                  34: 'Tomato___Spider_mites Two-spotted_spider_mite',
+                  35: 'Tomato___Target_Spot',
+                  36: 'Tomato___Tomato_Yellow_Leaf_Curl_Virus',
+                  37: 'Tomato___Tomato_mosaic_virus',
+                  38: 'Tomato___healthy'}

plant_disease_model_1_latest.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1a60ecd77e31d64dc726e1cca0ea43d0cbec0cf2088bb403f44f0e2720c23bb1
+size 210409423