Upload 12 files

.gitattributes

@@ -32,3 +32,4 @@ 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
+image/anthracnose.JPG filter=lfs diff=lfs merge=lfs -text

app.py

@@ -21,13 +21,18 @@ def main():
     class_name = ["健全","うどんこ病","灰色かび病","炭疽病","べと病","褐斑病","つる枯病","斑点細菌病","CCYV","モザイク病","MYSV"]
     
     # example
-    example=[
-            ['image/231305_20200302150233_01.JPG'],
-            ['image/0004_20181120084837_01.jpg'],
-            ['image/160001_20170830173740_01.JPG'],
-            ['image/152300_20190119175054_01.JPG'],
-            
-        ]
+    # example = [
+    #     'image/healthy.jpg',
+    #     'image/powdery.JPG',
+    #     'image/graymold.JPG',
+    #     'image/anthracnose.JPG',
+    #     'image/downy.JPG',
+    #     'image/cornespora.JPG',
+    #     'image/gummy.JPG',
+    #     'image/bacterial.JPG',
+    #     'image/ccyv.jpg',
+    #     'image/mosaic.jpg',
+    #     'image/mysv.jpg']
 
     # model定義
     model_ft = resnet18(num_classes = len(class_name),pretrained=False)
@@ -59,22 +64,48 @@ def main():
         return {class_name[i]: float(probs[i]) for i in range(labels_lenght)}
     
     
-    # 入力の形式を画像とする
-    inputs = gr.inputs.Image()
+    # # 入力の形式を画像とする
+    # inputs = gr.inputs.Image()
 
-    # 出力はラベル形式で，top5まで表示する
-    outputs = gr.outputs.Label(num_top_classes=5)
+    # # 出力はラベル形式で，top5まで表示する
+    # outputs = gr.outputs.Label(num_top_classes=5)
 
-    # サーバーの立ち上げ
-    interface = gr.Interface(fn=inference, 
-        inputs=[inputs], 
-        outputs=outputs,
-        examples=example,
-        title=title,
-        description=description)
+    # # サーバーの立ち上げ
+    # interface = gr.Interface(fn=inference, 
+    #     inputs=[inputs], 
+    #     outputs=outputs,
+    #     examples=example,
+    #     title=title,
+    #     description=description)
+    
+    with gr.Blocks(title="Cucumber Diseases Diagnosis",
+            css=".gradio-container {background:mintcream;}"
+        ) as demo:
+        gr.HTML("""<div style="font-family:'Arial', 'Serif'; font-size:18pt; text-align:center; color:black;">Cucumber Diseases Diagnosis</div>""")
+
+        with gr.Row(): 
+            input_image = gr.inputs.Image()      
+            output_label= gr.outputs.Label(num_top_classes=4)
+
+        send_btn = gr.Button("識別")
+        send_btn.click(fn=inference, inputs=input_image, outputs=output_label)
 
-    interface.launch()
+        with gr.Row():
+            # gr.Examples(['image/healthy.jpg'], label='cucumber', inputs=input_image)
+            gr.Examples(['image/healthy.jpg'], label='健全', inputs=input_image)
+            gr.Examples(['image/powdery.JPG'], label='うどんこ病', inputs=input_image)
+            gr.Examples(['image/graymold.JPG'], label='灰色かび病', inputs=input_image)
+            gr.Examples(['image/anthracnose.JPG'], label='炭疽病', inputs=input_image)
+            gr.Examples(['image/downy.JPG'], label='べと病', inputs=input_image)
+            gr.Examples(['image/cornespora.JPG'], label='褐斑病', inputs=input_image)
+            gr.Examples(['image/gummy.JPG'], label='つる枯病', inputs=input_image)
+            gr.Examples(['image/bacterial.JPG'], label='斑点細菌病', inputs=input_image)
+            gr.Examples(['image/ccyv.jpg'], label='CCYV', inputs=input_image)
+            gr.Examples(['image/mosaic.jpg'], label='モザイク病', inputs=input_image)
+            gr.Examples(['image/mysv.jpg'], label='MYSV', inputs=input_image)
 
+    demo.launch()
+      
 
 if __name__ == "__main__":
     main()