add app

.gitignore

@@ -0,0 +1,4 @@
+.ipynb_checkpoints
+flagged
+model_checkpoints
+saved_model

README.md

@@ -5,7 +5,7 @@ colorFrom: gray
 colorTo: green
 sdk: gradio
 sdk_version: 4.1.2
-app_file: app.py
+app_file: my_app.py
 pinned: false
 ---
 

classes.txt

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+apple_pie
+baby_back_ribs
+baklava
+beef_carpaccio
+beef_tartare
+beet_salad
+beignets
+bibimbap
+bread_pudding
+breakfast_burrito
+bruschetta
+caesar_salad
+cannoli
+caprese_salad
+carrot_cake
+ceviche
+cheesecake
+cheese_plate
+chicken_curry
+chicken_quesadilla
+chicken_wings
+chocolate_cake
+chocolate_mousse
+churros
+clam_chowder
+club_sandwich
+crab_cakes
+creme_brulee
+croque_madame
+cup_cakes
+deviled_eggs
+donuts
+dumplings
+edamame
+eggs_benedict
+escargots
+falafel
+filet_mignon
+fish_and_chips
+foie_gras
+french_fries
+french_onion_soup
+french_toast
+fried_calamari
+fried_rice
+frozen_yogurt
+garlic_bread
+gnocchi
+greek_salad
+grilled_cheese_sandwich
+grilled_salmon
+guacamole
+gyoza
+hamburger
+hot_and_sour_soup
+hot_dog
+huevos_rancheros
+hummus
+ice_cream
+lasagna
+lobster_bisque
+lobster_roll_sandwich
+macaroni_and_cheese
+macarons
+miso_soup
+mussels
+nachos
+omelette
+onion_rings
+oysters
+pad_thai
+paella
+pancakes
+panna_cotta
+peking_duck
+pho
+pizza
+pork_chop
+poutine
+prime_rib
+pulled_pork_sandwich
+ramen
+ravioli
+red_velvet_cake
+risotto
+samosa
+sashimi
+scallops
+seaweed_salad
+shrimp_and_grits
+spaghetti_bolognese
+spaghetti_carbonara
+spring_rolls
+steak
+strawberry_shortcake
+sushi
+tacos
+takoyaki
+tiramisu
+tuna_tartare
+waffles

my_app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+
+# Load your trained models
+model1 = tf.keras.models.load_model('model/FoodVisionFineTuneAug/')
+model2 = tf.keras.models.load_model('model/FoodVisionFineTune/')
+
+with open('classes.txt', 'r') as f:
+    classes = [line.strip() for line in f]
+
+# Add information about the models
+model1_info = """
+### Model 1 Information
+
+This model is based on the EfficientNetB0 architecture and was trained on the Food101 dataset.
+"""
+
+model2_info = """
+### Model 2 Information
+
+This model is based on the EfficientNetB0 architecture and was trained on augmented data, providing improved generalization.
+"""
+
+def preprocess(image: Image.Image):
+    # Convert numpy array to PIL Image
+    image = Image.fromarray((image * 255).astype(np.uint8))
+    image = image.resize((224, 224))  # replace with the input size of your models
+    image = np.array(image)
+    # image = image / 255.0  # normalize if you've done so while training
+    image = np.expand_dims(image, axis=0)
+    return image
+
+def predict(model_selection, image: Image.Image):
+    # Choose the model based on the dropdown selection
+    model = model1 if model_selection == "EfficentNetB0 Fine Tune" else model2
+
+    image = preprocess(image)
+    prediction = model.predict(image)
+    predicted_class = classes[np.argmax(prediction)]
+    confidence = np.max(prediction)
+    return predicted_class, confidence
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=[gr.Dropdown(["EfficentNetB0 Fine Tune", "EfficentNetB0 Fine Tune Augmented"]), gr.Image()],
+    outputs=[gr.Textbox(label="Predicted Class"), gr.Textbox(label="Confidence")],
+    title="Transfer Learning Mini Project",
+    description=f"{model1_info}\n\n{model2_info}",
+)
+
+iface.launch()

requirements.txt

@@ -0,0 +1,97 @@
+absl-py==2.0.0
+aiofiles==23.2.1
+altair==5.1.2
+annotated-types==0.6.0
+anyio==3.7.1
+astunparse==1.6.3
+attrs==23.1.0
+cachetools==5.3.2
+certifi==2023.7.22
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+contourpy==1.2.0
+cycler==0.12.1
+exceptiongroup==1.1.3
+fastapi==0.104.1
+ffmpy==0.3.1
+filelock==3.13.1
+flatbuffers==23.5.26
+fonttools==4.44.0
+fsspec==2023.10.0
+gast==0.5.4
+google-auth==2.23.4
+google-auth-oauthlib==1.0.0
+google-pasta==0.2.0
+gradio==4.1.2
+gradio_client==0.7.0
+grpcio==1.59.2
+h11==0.14.0
+h5py==3.10.0
+httpcore==1.0.1
+httpx==0.25.1
+huggingface-hub==0.19.0
+idna==3.4
+importlib-metadata==6.8.0
+importlib-resources==6.1.1
+Jinja2==3.1.2
+jsonschema==4.19.2
+jsonschema-specifications==2023.7.1
+keras==2.14.0
+kiwisolver==1.4.5
+libclang==16.0.6
+Markdown==3.5.1
+markdown-it-py==3.0.0
+MarkupSafe==2.1.3
+matplotlib==3.8.1
+mdurl==0.1.2
+ml-dtypes==0.2.0
+numpy==1.26.1
+oauthlib==3.2.2
+opt-einsum==3.3.0
+orjson==3.9.10
+packaging==23.2
+pandas==2.1.2
+Pillow==10.1.0
+protobuf==4.25.0
+pyasn1==0.5.0
+pyasn1-modules==0.3.0
+pydantic==2.4.2
+pydantic_core==2.10.1
+pydub==0.25.1
+Pygments==2.16.1
+pyparsing==3.1.1
+python-dateutil==2.8.2
+python-multipart==0.0.6
+pytz==2023.3.post1
+PyYAML==6.0.1
+referencing==0.30.2
+requests==2.31.0
+requests-oauthlib==1.3.1
+rich==13.6.0
+rpds-py==0.12.0
+rsa==4.9
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.16.0
+sniffio==1.3.0
+starlette==0.27.0
+tensorboard==2.14.1
+tensorboard-data-server==0.7.2
+tensorflow==2.14.0
+tensorflow-estimator==2.14.0
+tensorflow-intel==2.14.0
+tensorflow-io-gcs-filesystem==0.31.0
+termcolor==2.3.0
+tomlkit==0.12.0
+toolz==0.12.0
+tqdm==4.66.1
+typer==0.9.0
+typing_extensions==4.8.0
+tzdata==2023.3
+urllib3==2.0.7
+uvicorn==0.24.0.post1
+websockets==11.0.3
+Werkzeug==3.0.1
+wrapt==1.14.1
+zipp==3.17.0