run.py

labels = ['aircraft carrier',
 'airplane',
 'alarm clock',
 'ambulance',
 'angel',
 'animal migration',
 'ant',
 'anvil',
 'apple',
 'arm',
 'asparagus',
 'axe',
 'backpack',
 'banana',
 'bandage',
 'barn',
 'baseball bat',
 'baseball',
 'basket',
 'basketball',
 'bat',
 'bathtub',
 'beach',
 'bear',
 'beard',
 'bed',
 'bee',
 'belt',
 'bench',
 'bicycle',
 'binoculars',
 'bird',
 'birthday cake',
 'blackberry',
 'blueberry',
 'book',
 'boomerang',
 'bottlecap',
 'bowtie',
 'bracelet',
 'brain',
 'bread',
 'bridge',
 'broccoli',
 'broom',
 'bucket',
 'bulldozer',
 'bus',
 'bush',
 'butterfly',
 'cactus',
 'cake',
 'calculator',
 'calendar',
 'camel',
 'camera',
 'camouflage',
 'campfire',
 'candle',
 'cannon',
 'canoe',
 'car',
 'carrot',
 'castle',
 'cat',
 'ceiling fan',
 'cell phone',
 'cello',
 'chair',
 'chandelier',
 'church',
 'circle',
 'clarinet',
 'clock',
 'cloud',
 'coffee cup',
 'compass',
 'computer',
 'cookie',
 'cooler',
 'couch',
 'cow',
 'crab',
 'crayon',
 'crocodile',
 'crown',
 'cruise ship',
 'cup',
 'diamond',
 'dishwasher',
 'diving board',
 'dog',
 'dolphin',
 'donut',
 'door',
 'dragon',
 'dresser',
 'drill',
 'drums',
 'duck',
 'dumbbell',
 'ear',
 'elbow',
 'elephant',
 'envelope',
 'eraser',
 'eye',
 'eyeglasses',
 'face',
 'fan',
 'feather',
 'fence',
 'finger',
 'fire hydrant',
 'fireplace',
 'firetruck',
 'fish',
 'flamingo',
 'flashlight',
 'flip flops',
 'floor lamp',
 'flower',
 'flying saucer',
 'foot',
 'fork',
 'frog',
 'frying pan',
 'garden hose',
 'garden',
 'giraffe',
 'goatee',
 'golf club',
 'grapes',
 'grass',
 'guitar',
 'hamburger',
 'hammer',
 'hand',
 'harp',
 'hat',
 'headphones',
 'hedgehog',
 'helicopter',
 'helmet',
 'hexagon',
 'hockey puck',
 'hockey stick',
 'horse',
 'hospital',
 'hot air balloon',
 'hot dog',
 'hot tub',
 'hourglass',
 'house plant',
 'house',
 'hurricane',
 'ice cream',
 'jacket',
 'jail',
 'kangaroo',
 'key',
 'keyboard',
 'knee',
 'knife',
 'ladder',
 'lantern',
 'laptop',
 'leaf',
 'leg',
 'light bulb',
 'lighter',
 'lighthouse',
 'lightning',
 'line',
 'lion',
 'lipstick',
 'lobster',
 'lollipop',
 'mailbox',
 'map',
 'marker',
 'matches',
 'megaphone',
 'mermaid',
 'microphone',
 'microwave',
 'monkey',
 'moon',
 'mosquito',
 'motorbike',
 'mountain',
 'mouse',
 'moustache',
 'mouth',
 'mug',
 'mushroom',
 'nail',
 'necklace',
 'nose',
 'ocean',
 'octagon',
 'octopus',
 'onion',
 'oven',
 'owl',
 'paint can',
 'paintbrush',
 'palm tree',
 'panda',
 'pants',
 'paper clip',
 'parachute',
 'parrot',
 'passport',
 'peanut',
 'pear',
 'peas',
 'pencil',
 'penguin',
 'piano',
 'pickup truck',
 'picture frame',
 'pig',
 'pillow',
 'pineapple',
 'pizza',
 'pliers',
 'police car',
 'pond',
 'pool',
 'popsicle',
 'postcard',
 'potato',
 'power outlet',
 'purse',
 'rabbit',
 'raccoon',
 'radio',
 'rain',
 'rainbow',
 'rake',
 'remote control',
 'rhinoceros',
 'rifle',
 'river',
 'roller coaster',
 'rollerskates',
 'sailboat',
 'sandwich',
 'saw',
 'saxophone',
 'school bus',
 'scissors',
 'scorpion',
 'screwdriver',
 'sea turtle',
 'see saw',
 'shark',
 'sheep',
 'shoe',
 'shorts',
 'shovel',
 'sink',
 'skateboard',
 'skull',
 'skyscraper',
 'sleeping bag',
 'smiley face',
 'snail',
 'snake',
 'snorkel',
 'snowflake',
 'snowman',
 'soccer ball',
 'sock',
 'speedboat',
 'spider',
 'spoon',
 'spreadsheet',
 'square',
 'squiggle',
 'squirrel',
 'stairs',
 'star',
 'steak',
 'stereo',
 'stethoscope',
 'stitches',
 'stop sign',
 'stove',
 'strawberry',
 'streetlight',
 'string bean',
 'submarine',
 'suitcase',
 'sun',
 'swan',
 'sweater',
 'swing set',
 'sword',
 'syringe',
 't-shirt',
 'table',
 'teapot',
 'teddy-bear',
 'telephone',
 'television',
 'tennis racquet',
 'tent',
 'The Eiffel Tower',
 'The Great Wall of China',
 'The Mona Lisa',
 'tiger',
 'toaster',
 'toe',
 'toilet',
 'tooth',
 'toothbrush',
 'toothpaste',
 'tornado',
 'tractor',
 'traffic light',
 'train',
 'tree',
 'triangle',
 'trombone',
 'truck',
 'trumpet',
 'umbrella',
 'underwear',
 'van',
 'vase',
 'violin',
 'washing machine',
 'watermelon',
 'waterslide',
 'whale',
 'wheel',
 'windmill',
 'wine bottle',
 'wine glass',
 'wristwatch',
 'yoga',
 'zebra',
 'zigzag']

from PIL import Image 
import numpy as np
import tensorflow as tf

imgs = []
def predict(img):
    img = img['layers'][0][:,:,3]
    imgs.append(img)
    image_pil = Image.fromarray(img)

    # Resize the image using PIL
    new_size = (28, 28)  # Set the new size (e.g., 100x100)
    resized_image_pil = image_pil.resize(new_size)

    # Convert the resized PIL image back to a NumPy array
    resized_image_np = np.array(resized_image_pil)
    # imgs.append(img)
    img = np.array(resized_image_np).reshape(1, 28, 28,1)
    out = model.predict(img);
    top5 = np.argsort(out[0])[::-1][:5]
    label = labels

    # Create a dictionary with label-probability pairs for the top 5 predictions
    probabilities = {label[i]: float(out[0][i]) for i in top5}

    return probabilities

model = tf.keras.models.load_model('quickdraw.h5', compile=False)

import gradio as gr

gr.Interface(fn=predict,
             inputs=gr.Sketchpad(),
             outputs="label",
             live=True).launch()