Spaces:
Sleeping
Sleeping
| # examples = [["Examples/img1.png"], ["Examples/img2.png"],["Examples/img3.png"], ["Examples/img4.png"]] | |
| # import gradio as gr | |
| # import tensorflow as tf | |
| # import numpy as np | |
| # from tensorflow.keras.models import load_model | |
| # HEIGHT, WIDTH = 224, 224 | |
| # IMG_SIZE = 224 | |
| # model = load_model('Models/best_model1.h5') | |
| # def classify_image(inp): | |
| # NUM_CLASSES = 2 | |
| # labels = ['Cat', 'Dog'] | |
| # inp = tf.image.resize(inp, [IMG_SIZE, IMG_SIZE]) | |
| # inp = inp.numpy().reshape((-1, IMG_SIZE, IMG_SIZE, 3)) | |
| # inp = tf.keras.applications.vgg16.preprocess_input(inp) | |
| # prediction = model.predict(inp).flatten() | |
| # return {labels[i]: float(prediction[i]) for i in range(NUM_CLASSES)} # Fixed: return floats | |
| # image = gr.Image(height=HEIGHT, width=WIDTH, label='Input') | |
| # label = gr.Label(num_top_classes=2) | |
| # examples = [["Examples/img1.png"], ["Examples/img2.png"],["Examples/img3.png"], ["Examples/img4.png"]] | |
| # gr.Interface( | |
| # fn=classify_image, | |
| # inputs=image, | |
| # outputs=label, | |
| # title='Smart Pet Classifier', | |
| # examples=examples | |
| # ).launch(debug=False) | |
| import gradio as gr | |
| import tensorflow as tf | |
| import numpy as np | |
| from tensorflow.keras.models import load_model | |
| HEIGHT, WIDTH = 224, 224 | |
| IMG_SIZE = 224 | |
| model = load_model('Models/best_model1.h5') | |
| def classify_image(inp): | |
| labels = ['Cat', 'Dog'] | |
| inp = tf.image.resize(inp, [IMG_SIZE, IMG_SIZE]) | |
| inp = inp.numpy().reshape((-1, IMG_SIZE, IMG_SIZE, 3)) | |
| inp = tf.keras.applications.vgg16.preprocess_input(inp) | |
| prediction = model.predict(inp).flatten() | |
| if len(prediction) == 1: | |
| dog_prob = float(prediction[0]) | |
| return {labels[0]: 1 - dog_prob, labels[1]: dog_prob} | |
| else: | |
| return {labels[i]: float(prediction[i]) for i in range(len(labels))} | |
| image = gr.Image(height=HEIGHT, width=WIDTH, label='Input') | |
| label = gr.Label(num_top_classes=2) | |
| examples = [["Examples/img1.png"], ["Examples/img2.png"],["Examples/img3.png"], ["Examples/img4.png"]] | |
| gr.Interface( | |
| fn=classify_image, | |
| inputs=image, | |
| outputs=label, | |
| title='Smart Pet Classifier', | |
| # examples=examples | |
| ).launch(debug=False) |