Upload 15 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+apple_model_transferlearning.keras filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,61 @@
+import gradio as gr
+import tensorflow as tf
+print(tf.__version__)
+import numpy as np
+from PIL import Image
+
+import os
+
+#model_path = "apple_model_transferlearning.keras"
+model_path = r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\3_Model_Training_and_Application\apple_model_transferlearning.keras"
+print("Existiert die Modell-Datei?:", os.path.exists(model_path))
+model = tf.keras.models.load_model(model_path)
+
+
+
+def predict_pokemon(image):
+    # Preprocess image
+    print(type(image))
+    image = Image.fromarray(image.astype('uint8'))  # Convert numpy array to PIL image
+    image = image.resize((150, 150))  # Resize the image to 150x150 pixels
+    image = np.array(image)
+    image = np.expand_dims(image, axis=0)  # Add batch dimension
+
+    # Predict
+    prediction = model.predict(image)
+    # Convert the probabilities to rounded values
+    prediction = np.round(prediction, 2)
+
+    # Make sure the indices are correct according to your model's training
+    p_schorf        = prediction[0][0]   # Probability for "Schorf"
+    p_schwarzfaeule = prediction[0][1]   # Probability for "Schwarzfaeule"
+    p_zederapfel    = prediction[0][2]   # Probability for "Zederapfel"
+    p_gesund        = prediction[0][3]   # Probability for "Gesund"    
+
+    return {'gesund': p_gesund, 'schorf': p_schorf, 'schwarzfaeule': p_schwarzfaeule, 'zederapfel': p_zederapfel}
+
+ 
+ 
+# Create the Gradio interface
+input_image = gr.Image()
+iface = gr.Interface(
+    fn=predict_pokemon,
+    inputs=input_image,
+    outputs=gr.Label(),
+    examples=[r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Gesund1.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Gesund2.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Gesund3.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Schorf1.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Schorf2.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Schorf3.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Schwarzfaeule1.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Schwarzfaeule2.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Schwarzfaeule3.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Zederapfel1.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Zederapfel2.jpg",
+              r"C:\Users\dom-k\Visual Studio Code\6. Semester\Project1_Kupredom\Image_Classification\2_Data_collection\apple_images\model\Zederapfel3.jpg"],
+    description="Model")
+ 
+iface.launch()
+ 
+

apple_model_transferlearning.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fd3884cef0755965ce323e529a6633c3ff994590b2c2f39a3a32b6b0aec89cef
+size 250584735

requirements.txt

@@ -0,0 +1 @@
+tensorflow