from fastai.vision.all import * import gradio as gr import random __all__ = ['is_rock', 'learn', 'classify_image', 'determine_winner', 'play game' 'categories', 'image', 'label', 'examples', 'intf'] def is_rock(x): return x[0].issuper() learn = load_learner('RPS_model2.pkl') categories = ('paper', 'rock', 'scissors') def classify_image(img): pred, idx, probs = learn.predict(img) return dict(zip(categories, map(float, probs))) def determine_winner(user_choice, computer_choice): if user_choice == computer_choice: return "It's a tie!" elif (user_choice == 'rock' and computer_choice == 'scissors') or (user_choice == 'paper' and computer_choice == 'rock') or (user_choice == 'scissors' and computer_choice == 'paper'): return "You won!" else: return "Computer won!" def play_game(img): user_probs = classify_image(img) user_choice = max(user_probs, key=user_probs.get) computer_choice = random.choice(categories) winner = determine_winner(user_choice, computer_choice) computer_image = random.choice(get_image_files(f'{computer_choice}.jpg')) return f"User's choice: {user_choice}\nComputer's choice: {computer_choice}\n{winner}" image = gr.inputs.Image(shape=(192, 192)) label = gr.outputs.Label() #examples = ['rock.jpg', 'paper.jpg', 'scissor.jpg'] intf = gr.Interface(fn=play_game, inputs=image, outputs=[label, "image"]) intf.launch(inline=False)