Zeeshan01 commited on
Commit
0b4029e
·
1 Parent(s): 395eb87

Upload folder using huggingface_hub

Browse files
Files changed (7) hide show
  1. README.md +1 -7
  2. __pycache__/app.cpython-310.pyc +0 -0
  3. app.py +58 -0
  4. b1.png +0 -0
  5. b2.png +0 -0
  6. model/BreastCancer.h5 +3 -0
  7. requirements.txt +3 -0
README.md CHANGED
@@ -1,12 +1,6 @@
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  ---
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  title: BCancer
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- emoji: 😻
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- colorFrom: red
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- colorTo: blue
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  sdk: gradio
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  sdk_version: 3.35.2
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- app_file: app.py
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- pinned: false
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  ---
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-
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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  ---
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  title: BCancer
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+ app_file: app.py
 
 
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  sdk: gradio
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  sdk_version: 3.35.2
 
 
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  ---
 
 
__pycache__/app.cpython-310.pyc ADDED
Binary file (1.14 kB). View file
 
app.py ADDED
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+ import gradio as gr
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+ import tensorflow as tf
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+ import numpy as np
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+ from PIL import Image
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+
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+
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+
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+
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+
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+
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+ # Initial parameters for pretrained model
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+ IMG_SIZE = 300
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+
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+ labelsBreast = {'Benign':0,
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+ 'Malignant':1,
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+ 'Normal':2}
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+
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+ # Load the model from the H5 file
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+ model = tf.keras.models.load_model('model/BreastCancer.h5')
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+
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+ # Define the prediction function
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+ def predict(img):
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+ img_height = 224
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+ img_width = 224
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+
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+ # Convert the NumPy array to a PIL Image object
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+ pil_img = Image.fromarray(img)
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+
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+ # Resize the image using the PIL Image object
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+ pil_img = pil_img.resize((img_height, img_width))
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+
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+ # Convert the PIL Image object to a NumPy array
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+ x = tf.keras.preprocessing.image.img_to_array(pil_img)
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+
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+ x = x.reshape(1, img_height, img_width, 3)
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+ np.set_printoptions(formatter={'float': '{: 0.3f}'.format})
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+
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+
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+ predi = model.predict(x)
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+ accuracy_of_class = '{:.1f}'.format(predi[0][np.argmax(predi)] * 100) + "%"
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+ classes = list(labelsBreast.keys())[np.argmax(predi)]
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+ context = {
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+ 'predictedLabel': classes,
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+ # 'y_class': y_class,
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+ # 'z_class': z_class,
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+ 'accuracy_of_class': accuracy_of_class
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+ }
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+
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+
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+
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+ return context
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+
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+
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+
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+ demo = gr.Interface(fn=predict, inputs="image", outputs="text" , examples=[["b1.png"],["b2.png"]],)
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+
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+ demo.launch()
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+
b1.png ADDED
b2.png ADDED
model/BreastCancer.h5 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:9a2d31cc5eed3d9ad783f825e5233ad0c983d033de76d28581bb510d3d2d67ff
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+ size 177263680
requirements.txt ADDED
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+ tensorflow
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+ numpy
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+ pillow