hi there

allheroes2.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:da6bbcef6ec074810f8655f04feb12a965e5c1680ac5f0c7397046adc3283e67
+size 87548919

app.py

@@ -0,0 +1,52 @@
+import sys
+import pathlib
+
+# Patch for non-Windows systems: use PosixPath in place of WindowsPath
+if sys.platform != "win32":
+    pathlib.WindowsPath = pathlib.PosixPath
+
+
+import fastai
+print(f"FastAI Version: {fastai.__version__}")
+from fastai.vision.all import *
+import fastcore
+
+# Load the model
+learn = load_learner('D:/AI/projects/marvel2/allheroes2.pkl')
+categories = [
+    'Adam Warlock', 'Black Panther', 'Black Widow', 'Bruce Banner', 
+    'Captain America', 'Cloak & Dagger', 'Doctor Strange', 'Groot', 
+    'Hawkeye', 'Hela', 'Invisible Woman', 'Iron Fist', 'Iron Man', 
+    'Jeff', 'Loki', 'Luna Snow', 'Magik', 'Magneto', 'Mantis', 
+    'Mister Fantastic', 'Moon Knight', 'Namor', 'Peni Parker', 
+    'Psylocke', 'Rocket Raccoon', 'Scarlet Witch', 'Spider Man', 
+    'Squirrel Girl', 'Star Lord', 'Storm', 'The Hulk', 'The Punisher', 
+    'Thor', 'Venom', 'Winter Soldier', 'Wolverine',]
+
+# Define the prediction function
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# Gradio interface
+import gradio as gr
+
+# Define the input and output components
+image = gr.Image(height=192, width=192)  # Resize input images to 192x192
+label = gr.Label() 
+examples =  ['2.jpg', 'black6.jpg', 'fist4jpg', 'wol2.jpg','groot4']
+
+# Create the Gradio app
+demo = gr.Interface(
+    fn=classify_image, 
+    inputs=image, 
+    outputs=label, 
+    examples=examples,
+    title="Marvel Rivals Hero Classifier",
+    description=(
+        "This classifier recognizes every Marvel Rivals hero, insert an image or use one of the images to try it out"
+    )
+)
+
+# Launch the app
+demo.launch()

requirements.text

@@ -0,0 +1,3 @@
+fastai==2.7.18
+gradio==5.12.0
+