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Final_Chicken_disease_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e6fbc0b00b8e4d86b50707fcb39a39f99eecccdb6f4732ea53cdfee793a052c4
+size 234256896

app.py

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+import keras
+from keras.models import load_model
+import gradio as gr
+import cv2
+
+my_model=load_model('Final_Chicken_disease_model.h5',compile=True)
+auth_model=load_model('auth_model.h5',compile=True)
+name_disease={0:'Coccidiosis',1:'Healthy',2:'New Castle Disease',3:'Salmonella'}
+result={0:'Critical',1:'No issue',2:'Critical',3:'Critical'}
+recommend={0:'Panadol',1:'You have no need Medicine',2:'Percetamol',3:'Ponston'}
+
+
+def predict(image):
+  image_check=cv2.resize(image,(224,224))
+  indx=auth_model.predict(image_check.reshape(1,224,224,3)).argmax()
+  if indx==0:
+      image=cv2.resize(image,(224,224))
+      indx=my_model.predict(image.reshape(1,224,224,3)).argmax()
+      name=name_disease.get(indx)
+      status=result.get(indx)
+      recom=recommend.get(indx)
+      return name,status,recom
+  else:
+      name='Unkown Image'
+      status='N/A'
+      recom='N/A'
+      return name,status,recom
+
+
+interface=gr.Interface(fn=predict,inputs=[gr.Image(label='upload Image')],outputs=[gr.components.Textbox(label="Disease Name"),gr.components.Textbox(label="result"),gr.components.Textbox(label='Medicine Recommend')],
+                      examples=[['disease.jpg'],['ncd.jpg'],['hredirect2.webp']])
+interface.launch(debug=True)
+
+
+
+
+

auth_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:55ca5e07d8f4d45eab021364be749ced18402f85f5edb7425486ed76ea5c3093
+size 234256896

requirements.txt

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+tensorflow==2.12.0
+keras
+opencv-python