Push model

app.py

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+import gradio as gr
+import numpy as np
+
+import torch
+import torchvision.models as models
+
+from torchvision import transforms
+from PIL import Image
+import joblib
+import pickle
+
+# Load the classifier
+
+classifier = joblib.load('logistic_model.pkl')
+
+# Load label mappings
+
+label_to_number, number_to_label = pickle.load(open('label_mappings.pkl', 'rb'))
+
+# Load a pretrained ResNet model
+model = models.resnet50(pretrained=True)
+model = torch.nn.Sequential(*list(model.children())[:-1])  # Remove the classification layer
+model.eval()
+
+# Define image preprocessing
+transform = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+    transforms.Normalize(
+        mean=[0.485, 0.456, 0.406], 
+        std=[0.229, 0.224, 0.225]
+    ),
+])
+
+# Function to extract embedding
+def get_embedding(image_path):
+    image = Image.open(image_path).convert('RGB')
+    image = transform(image).unsqueeze(0)  # Add batch dimension
+    with torch.no_grad():
+        embedding = model(image).squeeze()  # Remove extra dimensions
+    return embedding.numpy()
+
+# Prediction function
+def classify_image(image):
+    embedding = get_embedding(image).reshape(1, -1)
+    pred = classifier.predict(embedding)
+    prob = classifier.predict_proba(embedding)
+    pred_label = pred[0]
+    pred_index = list(classifier.classes_).index(pred_label)
+    confidence = prob[0][pred_index]
+    return f"{number_to_label[pred_label]} ({confidence * 100:.2f}%)"
+
+# Gradio UI
+demo = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Mushroom Spore Classifier",
+    description="Upload a thumbnail of a mushroom spore and get its predicted class."
+)
+
+if __name__ == "__main__":
+    demo.launch()

knn_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c859faae2b30a52f9f5fd6a755b7373d03600318086c0f5584082e2d8a4673bb
+size 11242916

label_mappings.npz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a11339a3c3ec38e7c4c4e94e0555c30576626746c52655e51b9bb644a0fd025e
+size 52930

label_mappings.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a2cbb2b6149096a433ad7848dbca0d89bdbe8651c8e925e57c051835a7772979
+size 33190

logistic_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5cf9d4e355e2df40988bf6ad6b0ec17ecc5ba453263ac7ea33255da367f09498
+size 16663239

requirements.txt

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+gradio
+torch
+torchvision
+numpy
+scikit-learn
+Pillow
+joblib