Duplicate from ahmedxeno/kidney_disease_classification_CT_scan

Co-authored-by: ahmed kamran <ahmedxeno@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+title: Kidney Disease Classification CT Scan
+emoji: 🏢
+colorFrom: indigo
+colorTo: green
+sdk: gradio
+sdk_version: 3.17.0
+app_file: app.py
+pinned: false
+duplicated_from: ahmedxeno/kidney_disease_classification_CT_scan
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+
+import gradio as gr
+import tensorflow as tf 
+import tensorflow.keras 
+import matplotlib.pyplot as plt
+import cv2
+import tensorflow_io as tfio
+import numpy as np
+
+loaded_model = tf.keras.models.load_model( 'kidney2.h5')
+
+def take_img(img):
+  
+  resize = tf.image.resize(img, (224,224))
+  gray = tfio.experimental.color.bgr_to_rgb(resize)
+  yhat = loaded_model.predict(np.expand_dims(gray/255, 0))
+  label_names = {
+  "1": "Cyst",
+  "2": "Normal",
+  "3": "Stone",
+  "4": "Tumor"    
+  }
+  classes_x=np.argmax(yhat,axis=1)
+  a = classes_x[0]
+  input_value = a + 1
+  input_str = str(input_value)
+  predicted_label = label_names[input_str]
+  q= yhat[0][0]
+  w = yhat[0][1]
+  e = yhat[0][2]
+  r = yhat[0][3] 
+
+  q = str(q)
+  w = str(w)
+  e = str(e)
+  r = str(r)  
+ 
+  return {'cryst' : q ,'Normal' : w ,'Stone' : e ,'Tumour' : r }
+
+
+
+image = gr.inputs.Image(shape=(224,224))
+
+label = gr.outputs.Label('ok')
+gr.Interface(fn=take_img, inputs=image, outputs="label",interpretation='default').launch(debug='True')

kidney2.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:418f1e1b04f1028ce640b584940e2689e406950ba2d1b65a978333275c9e2264
+size 9404184

requirements.txt

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+tensorflow
+opencv-python
+tensorflow_io
+numpy
+gradio