diff --git a/.gitattributes b/.gitattributes
index a7c807c8fc995381d4ada05ab268c67edfe72097..a4e523355e930de73fb303949b248a7ed6dfb3b8 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -35,4 +35,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 export.pkl filter=lfs diff=lfs merge=lfs -text
 ignore flagged folder
-
+Images/PKG[[:space:]]-[[:space:]]Breast-Metastases-MSKCC filter=lfs diff=lfs merge=lfs -text
+Images/PKG[[:space:]]-[[:space:]]CPTAC-BRCA filter=lfs diff=lfs merge=lfs -text
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diff --git a/Images/PKG - CPTAC-BRCA/BRCA/03BR008-a502dc7b-55ac-4828-8808-6dae2a.jpeg b/Images/PKG - CPTAC-BRCA/BRCA/03BR008-a502dc7b-55ac-4828-8808-6dae2a.jpeg
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diff --git a/app.py b/app.py
index fa0e367f57e41aadaa701e01ce17f829263897a7..6ed668716c8d4b79e14df58eae7e1f7cb05f3151 100644
--- a/app.py
+++ b/app.py
@@ -3,8 +3,9 @@ from fastai.vision.all import *
 import skimage
 
 learn = load_learner('export.pkl')
-
+examples = [['Images/PKG - Breast-Metastases-MSKCC/Breast-Metastases-MSKCC/HobI16-053768896760.jpeg'], ['Images/PKG - CPTAC-BRCA/BRCA/01BR001-4ffefc66-d0ba-4a36-b4fa-35bd91.jpeg']]
 labels = learn.dls.vocab
+
 def predict(img):
     img = PILImage.create(img)
     pred,pred_idx,probs = learn.predict(img)
@@ -16,4 +17,4 @@ article="<p style='text-align: center'><a href='https://www.kaggle.com/code/jose
 interpretation='default'
 enable_queue=True
 
-gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=6),title=title,description=description,article=article,interpretation=interpretation,enable_queue=enable_queue).launch()
\ No newline at end of file
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=6),title=title,description=description,article=article,examples=examples , interpretation=interpretation,enable_queue=enable_queue).launch()
\ No newline at end of file
diff --git a/export.pkl b/export.pkl
index 109e4604e7bfe00d1b86bd5d098488d0b1c862d0..cc9585e847c7c92f2e193af2608925610c0b10d7 100644
--- a/export.pkl
+++ b/export.pkl
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:afa9c7a869d51d75d883512e7d009c7f5b375070badc0fc65c1a34643583d9c3
-size 102891404
+oid sha256:4c76c41cd7b02c2445405c3c6cb52fe3a51658bbbe37e3381ec21850677a3c78
+size 102888957
diff --git a/train.py b/train.py
new file mode 100644
index 0000000000000000000000000000000000000000..fdbf0bc649a72908c1c72647d0bef7c27c8f3737
--- /dev/null
+++ b/train.py
@@ -0,0 +1,46 @@
+import os
+import slideio
+from PIL import Image
+
+
+####################Convert SVS files to JPEG files####################
+# Set the path to the svs files
+svs_path = "/Users/josedelgado/Downloads/"
+
+# Set the path to the output directory
+output_path = "/Users/josedelgado/Documents/GitHub/microbiology/Images"
+
+# Set the size of the representative image
+size = (224, 224)
+
+# Loop through the svs files
+for root, dirs, files in os.walk(svs_path):
+    for filename in files:
+        if filename.endswith(".svs"):
+            print("processing " + os.path.join(root, filename)  )
+            # Open the svs file
+            slide = slideio.open_slide(os.path.join(root, filename))
+
+            # Read a representative image from the slide
+            scene = slide.get_scene(0)
+            print("region size: " + str(scene.size))
+
+            # Convert the image to RGB format
+            image = scene.read_block(size=(500,0))
+
+            # Set the output filename
+            output_filename = os.path.splitext(filename)[0] + ".jpeg"
+
+            # Set the output directory
+            output_dir = os.path.join(output_path, os.path.relpath(root, svs_path))
+
+            # Create the output directory if it doesn't exist
+            if not os.path.exists(output_dir):
+                os.makedirs(output_dir)
+
+            # Convert the numpy array to a PIL image
+            image = Image.fromarray(image)
+
+            # Save the image in the ImageNet file folder format
+            output_file = os.path.join(output_dir, output_filename)
+            image.save(output_file)
\ No newline at end of file