update

.vscode/launch.json

@@ -0,0 +1,20 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python: Pytest",
+            "type": "python",
+            "request": "launch",
+            "module": "pytest",
+            "args": ["tests/test_api.py"],
+            "console": "integratedTerminal",
+            "justMyCode": false,
+            "env": {
+                "PYTHONASYNCIODEBUG": "1"
+            }
+        }
+    ]
+}

.vscode/settings.json

@@ -0,0 +1,8 @@
+{
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter"
+    },
+    "python.formatting.provider": "none",
+    "python.testing.pytestEnabled": true,
+    "python.testing.unittestEnabled": false,
+}

app.py

@@ -1,10 +1,11 @@
 import gradio
 from model.model import Model
-from numpy.typing import ArrayLike
 
-def main(processed_image: ArrayLike):
+def main(list_encoded_image: str):
+    np.array(json.loads(list_encoded_image))
     model = Model()
-    model.detect_object(processed_image)
+    processed_image
+    # model.detect_object(processed_image)
 
 gradio_interface = gradio.Interface(fn=main, inputs="text", outputs="text")
 gradio_interface.launch()

tests/test_model.py

@@ -4,7 +4,7 @@ import os
 import numpy as np
 import pytest
 
-from object_detection_model.model import Model, ModelConfig
+from model.model import Model
 
 
 @pytest.fixture
@@ -17,13 +17,7 @@ def test_detect_objects(sample_img_url: str):
     with open(sample_img_url, "rb") as image_file:
         image_bytes = io.BytesIO(image_file.read()).read()
     processed_image = np.frombuffer(image_bytes, dtype=np.uint8)
-
-    model = Model(
-        ModelConfig(
-            config_file_path="object_detection_model/model_files/ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt",
-            frozen_model_path="object_detection_model/model_files/frozen_inference_graph.pb",
-            labels_path="object_detection_model/model_files/coco.names",
-        )
-    )
+    
+    model = Model()
     model.detect_object(data=processed_image)
     assert type(image_bytes) == bytes