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.gitattributes

@@ -32,3 +32,13 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+8.png filter=lfs diff=lfs merge=lfs -text
+10.png filter=lfs diff=lfs merge=lfs -text
+15.png filter=lfs diff=lfs merge=lfs -text
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+37.png filter=lfs diff=lfs merge=lfs -text
+48.png filter=lfs diff=lfs merge=lfs -text
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+82.png filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+title: Retinal Disease
+emoji: 🐠
+colorFrom: pink
+colorTo: blue
+sdk: gradio
+sdk_version: 2.9.4
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

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+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+import cv2
+import keras
+import gradio as gr
+
+SHAPE = (224, 224, 3)
+
+predictor_disease_risk = keras.models.load_model('predictor_Disease_Risk.h5')
+predictor_dr = keras.models.load_model('predictor_DR.h5')
+predictor_mh = keras.models.load_model('predictor_MH.h5')
+predictor_odc = keras.models.load_model('predictor_ODC.h5')
+predictor_tsln = keras.models.load_model('predictor_TSLN.h5') 
+predictor_dn = keras.models.load_model('predictor_DN.h5')
+predictor_armd = keras.models.load_model('predictor_ARMD.h5')
+predictor_mya = keras.models.load_model('predictor_MYA.h5')
+predictor_brvo = keras.models.load_model('predictor_BRVO.h5')
+
+
+def cut_and_resize(image):
+  LOW_TOL = 20
+  img_bw = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+  img_bw[img_bw<=LOW_TOL] = 0
+  y_nonzero, x_nonzero = np.nonzero(img_bw)
+  image = image[np.min(y_nonzero):np.max(y_nonzero), np.min(x_nonzero): np.max(x_nonzero), ]
+  return cv2.resize(image, SHAPE[:2], interpolation = cv2.INTER_LINEAR)
+ 
+def simple_normalizer(X):
+  return X / 255.0
+
+def predict (image_path):
+  image = simple_normalizer(cut_and_resize(cv2.imread(image_path)))
+  result = predictor_disease_risk.predict(np.array([image]))[0][0] 
+  
+  dr = predictor_dr.predict(np.array([image]))[0][0]  
+  mh = predictor_mh.predict(np.array([image]))[0][0]
+  odc = predictor_odc.predict(np.array([image]))[0][0] 
+  tsln = predictor_tsln.predict(np.array([image]))[0][0]
+  dn = predictor_dn.predict(np.array([image]))[0][0]
+  armd = predictor_armd.predict(np.array([image]))[0][0]
+  mya = predictor_mya.predict(np.array([image]))[0][0]
+  brvo = predictor_brvo.predict(np.array([image]))[0][0]
+  
+  diseases = {
+      'DR'  : float(dr),
+      'MH'  : float(mh),
+      'ODC' : float(odc),
+      'DN'  : float(dn),
+      'TSLN': float(tsln),
+      'ARMD': float(armd),
+      'MYA' : float(mya),
+      'BRVO': float(brvo)    
+  }
+  
+  to_delete = []
+  for k,v in diseases.items():
+    if v < 0.05:
+      to_delete.append(k)
+  
+  for k in to_delete:
+    del diseases[k]
+  
+  if len(diseases) == 0:
+    diseases = {'No specific disease': 0.0}
+  
+  
+  return (
+    {'Enferma': float(result), 'Sana': 1 - float(result)}, diseases
+  )
+ 
+title = 'Retinal Disease Predictor'
+description = 'Modelo de deep learning que permite clasificar imágenes de la retina en patológicas y no patológicas. Si detecta una retina enferma, realiza un diagnóstico de la enfermedad concreta entre las siguientes: Diabetic Retinopathy (DR), Media Haze (MH), Optic Disk Cupping (ODC), Drusen (DN), Tessellation (TSLN), Age Related Macular Disease (ARMD), Myopia (MYA), Branch Retinal Vein Occlusion (BRVO)  . Las imágenes deben tener fondo negro.'
+article = 'Proyecto HORUS (Helping Oftalmoscopy of Retina Using Supervised Learning'
+
+interface = gr.Interface(
+  predict,
+  inputs = [gr.inputs.Image(source="upload",type="filepath", label="Imagen")],
+  outputs= [gr.outputs.Label(num_top_classes=2, label='Retina'), gr.outputs.Label(num_top_classes=4, label='Enfermedad')],
+  title = title, description = description, article = article,
+  theme = 'peach',
+  examples = ['10.png', '82.png', '15.png', '25.png', '48.png', '61.png', '37.png', '631.png', '23.png', '8.png']
+)
+
+interface.launch()

predictor_ARMD.h5

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+size 97691248

predictor_BRVO.h5

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predictor_DN.h5

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predictor_DR.h5

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predictor_Disease_Risk.h5

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predictor_MH.h5

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predictor_MYA.h5

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predictor_ODC.h5

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predictor_TSLN.h5

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requirements.txt

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+opencv-python==4.1.2.30
+tensorflow

índice.gitattributes

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+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
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