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README.md

@@ -1,10 +1,10 @@
 ---
-title: BioTech
-emoji: 📉
+title: Plant Test Demo
+emoji: 👁
 colorFrom: red
-colorTo: purple
+colorTo: indigo
 sdk: gradio
-sdk_version: 5.49.1
+sdk_version: 5.44.1
 app_file: app.py
 pinned: false
 ---

app.py

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+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+import json
+
+# Load TFLite model
+interpreter = tf.lite.Interpreter(model_path="plant_disease_model.tflite")
+interpreter.allocate_tensors()
+input_details = interpreter.get_input_details()
+output_details = interpreter.get_output_details()
+
+# Load labels
+with open("class_labels.json") as f:
+    labels = json.load(f)
+
+def predict(img):
+    if isinstance(img, np.ndarray):
+        img = Image.fromarray(img)
+    img = img.resize((224, 224))  # adjust size to your model
+    img = np.array(img, dtype=np.float32) / 255.0
+    img = np.expand_dims(img, axis=0)
+
+    interpreter.set_tensor(input_details[0]['index'], img)
+    interpreter.invoke()
+    output_data = interpreter.get_tensor(output_details[0]['index'])
+
+    pred_class = int(np.argmax(output_data[0]))
+    print("Input shape:", img.shape)
+    print("Input dtype:", img.dtype)
+    print("Output:", output_data)
+    print("Predicted class:", pred_class)
+    print("Label:", labels[str(pred_class)])
+    return labels[str(pred_class)]
+    
+
+demo = gr.Interface(fn=predict, inputs="image", outputs="label")
+demo.launch()

class_labels.json

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+{
+  "0": "Apple___Apple_scab",
+  "1": "Apple___Black_rot",
+  "2": "Apple___Cedar_apple_rust",
+  "3": "Apple___healthy",
+  "4": "Blueberry___healthy",
+  "5": "Cherry_(including_sour)___Powdery_mildew",
+  "6": "Cherry_(including_sour)___healthy",
+  "7": "Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot",
+  "8": "Corn_(maize)___Common_rust_",
+  "9": "Corn_(maize)___Northern_Leaf_Blight",
+  "10": "Corn_(maize)___healthy",
+  "11": "Grape___Black_rot",
+  "12": "Grape___Esca_(Black_Measles)",
+  "13": "Grape___Leaf_blight_(Isariopsis_Leaf_Spot)",
+  "14": "Grape___healthy",
+  "15": "Orange___Haunglongbing_(Citrus_greening)",
+  "16": "Peach___Bacterial_spot",
+  "17": "Peach___healthy",
+  "18": "Pepper,_bell___Bacterial_spot",
+  "19": "Pepper,_bell___healthy",
+  "20": "Potato___Early_blight",
+  "21": "Potato___Late_blight",
+  "22": "Potato___healthy",
+  "23": "Raspberry___healthy",
+  "24": "Soybean___healthy",
+  "25": "Squash___Powdery_mildew",
+  "26": "Strawberry___Leaf_scorch",
+  "27": "Strawberry___healthy",
+  "28": "Tomato___Bacterial_spot",
+  "29": "Tomato___Early_blight",
+  "30": "Tomato___Late_blight",
+  "31": "Tomato___Leaf_Mold",
+  "32": "Tomato___Septoria_leaf_spot",
+  "33": "Tomato___Spider_mites Two-spotted_spider_mite",
+  "34": "Tomato___Target_Spot",
+  "35": "Tomato___Tomato_Yellow_Leaf_Curl_Virus",
+  "36": "Tomato___Tomato_mosaic_virus",
+  "37": "Tomato___healthy"
+}

gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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+images/space.jpg.webp filter=lfs diff=lfs merge=lfs -text
+images/images/city.jpg.webp filter=lfs diff=lfs merge=lfs -text

plant_disease_model.tflite

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ef97f1c425b68c37ec676a5555a4d2da3c36895be86e166e4ab558c65169c04f
+size 12950792

requirements.txt

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+gradio
+tensorflow
+pillow
+numpy