version1

app.py

@@ -1,7 +1,36 @@
 import gradio as gr
+from fastai.vision.all import *
+from fastcore.all import *
 
-def greet(name):
-    return "Hello " + name + "!!"
+learn = load_learner("model1.pkl")
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+categories = ('Simmental','Holstein',"Hereford","Angus","Charolais","Limousin","Jersey","Brown Swiss")
+
+def classify_img(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+with gr.Blocks(title = "ineğin türü nedir? ") as demo:
+    with gr.Row():
+        gr.Markdown("""
+                     ## inek türü  Tespiti
+                     #### Bilgisayarınızdan yada telefonunuzdan resim yükleyin
+                     #### Denemek amaçlı örneklere çift tıklayın ve Tahmin Et tuşuna basın
+                     """)
+    with gr.Row():
+        image = gr.inputs.Image(shape=(192,192))   
+    with gr.Row():
+        output = gr.outputs.Label()      
+    with gr.Row():
+        image_button = gr.Button("Tahmin Et")
+        image_button.click(classify_img, inputs=image, outputs=output)
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Examples(inputs=image,examples=["1.jpg"],label="angus")
+        with gr.Column():
+            gr.Examples(inputs=image,examples=["2.jpg"],label="jersey")
+        with gr.Column():
+            gr.Examples(inputs=image,examples=["3.jpg"],label="simmental")
+    
+demo.launch()   

model1.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:44219f03e5f9729494839f5e3b20d49de3f4360441e6e5ff4c49b3afbf72de0e
+size 46970543

requirements.txt

@@ -0,0 +1 @@
+fastai