update gradio server port

Dockerfile

@@ -15,10 +15,8 @@ COPY ./requirements.txt /code/requirements.txt
 
 RUN apt-get install -y python3 python3-pip
 
-# RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
-RUN pip install --upgrade -r /code/requirements.txt
-
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
 
 COPY . .
 
-CMD ["python3", "app.py", "--host", "0.0.0.0", "--port", "7860"]
+CMD ["python3", "app.py"]

app.py

@@ -11,14 +11,12 @@ class Pix2StructForRegression(nn.Module):
     def __init__(self, sourcemodel_path, device):
         super(Pix2StructForRegression, self).__init__()
         self.model = Pix2StructVisionModel.from_pretrained(sourcemodel_path)
-        print("Pix2StructForRegression Model is Loaded...")
         self.regression_layer1 = nn.Linear(768, 1536)
         self.dropout1 = nn.Dropout(0.1)
         self.regression_layer2 = nn.Linear(1536, 768)
         self.dropout2 = nn.Dropout(0.1)
         self.regression_layer3 = nn.Linear(768, 2)
         self.device = device
-        print("Regression Layers are Loaded...")
 
     def forward(self, *args, **kwargs):
         outputs = self.model(*args, **kwargs)
@@ -32,16 +30,13 @@ class Pix2StructForRegression(nn.Module):
         return regression_output
 
     def load_state_dict_file(self, checkpoint_path, strict=True):
-        print("Loading Model Weights...")
         state_dict = torch.load(checkpoint_path, map_location=self.device)
         self.load_state_dict(state_dict, strict=strict)
-        print("Model Weights are Loaded...")
 
 class Inference:
     def __init__(self) -> None:
         self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-        self.model, self.processor = self.load_model_and_processor("matcha-base", "model/pta-text-v0.1.pt")
-        print("Model and Processor are Loaded...")
+        self.model, self.processor = self.load_model_and_processor("google/matcha-base", "model/pta-text-v0.1.pt")
 
     def load_model_and_processor(self, model_name, checkpoint_path):
         model = Pix2StructForRegression(sourcemodel_path=model_name, device=self.device)
@@ -84,7 +79,6 @@ class Inference:
 
     def draw_circle_on_image(self, image, coordinates):
         x, y = coordinates[0] * image.width, coordinates[1] * image.height
-        print(coordinates)
         draw = ImageDraw.Draw(image)
         radius = 5
         draw.ellipse((x-radius, y-radius, x+radius, y+radius), fill="red")
@@ -99,7 +93,6 @@ class Inference:
 
 def main():
     inference = Inference()
-    print("Model and Processor are Loaded...")
     # Gradio Interface
     iface = gr.Interface(
         fn=inference.process_image_and_draw_circle,
@@ -110,7 +103,8 @@ def main():
         description="Upload an image and enter a prompt to see the model's prediction."
     )
 
+    iface.launch(server_name="0.0.0.0", port=7860)
+    
 
-    iface.launch()
 if __name__ == "__main__":
     main()