type

Dockerfile

@@ -0,0 +1,14 @@
+FROM python:3.9-slim-bullseye
+
+
+WORKDIR /app
+
+COPY requirements.txt requirements.txt
+
+RUN pip3 install -r requirements.txt
+
+COPY app.py .
+
+COPY img /app/img
+
+CMD [ "python3", "-m" , "app.py"]

Pipfile

@@ -6,7 +6,7 @@ name = "pypi"
 [packages]
 gradio = "==3.35.2"
 numpy = "==1.23.3"
-tensorflow = "==2.12.0"
+tensorflow = "==2.9.1"
 
 [dev-packages]
 

app.py

@@ -19,18 +19,18 @@ class_names=["Black Sea Sprat",
  "Trout"]
 
 
-def preprocess_image(img, label):
+def preprocess_image(img):
     img = load_img(img, target_size=(249, 249, 3))
     img = image.img_to_array(img)
     img = np.expand_dims(img, axis=0)
     img /= 255.0
     print(img.shape)
-    return img, label
+    return img
 
 
 
 def predict(img):
-    img, _ = preprocess_image(img, 1)
+    img = preprocess_image(img)
     pred = model.predict(img)
     pred = np.squeeze(pred).astype(float)
     print(pred)
@@ -55,4 +55,4 @@ demo = gr.Interface(
     title="fish classification",
 )
 
-demo.launch()
+demo.launch(server_name="0.0.0.0", server_port=7000)

requirements.txt

@@ -1,3 +1,3 @@
-gradio==3.35.2
+gradio==3.39.0
 numpy==1.23.3
-tensorflow==2.12.0
+tensorflow==2.9.1