CV app docker fix

app_cv/Dockerfile

@@ -18,11 +18,10 @@ RUN curl "https://drive.usercontent.google.com/download?id=1lHTrW1rmYoYnMSUlhLwq
 
 COPY . .
 RUN pip install --no-cache-dir -r requirements.txt
-
-EXPOSE 5000
+RUN pip freeze
 
 # CMD ["gunicorn", "--bind", "0.0.0.0:5000", "--workers", "2", "app:app"]
-CMD ["uvicorn", "--port", "5000", "--workers", "2", "app:app"]
+CMD ["uvicorn", "--host", "0.0.0.0", "--port", "5000", "--workers", "1", "--log-level", "info", "app:app"]
 
 # docker build -t fetcher_cv .
 # docker run --rm -p 5000:5000 fetcher_cv

app_cv/app.py

@@ -6,7 +6,7 @@ import numpy as np
 import cv2
 import traceback
 import logging
-logging.basicConfig(level=logging.DEBUG, format='%(asctime)s [%(levelname)s] %(message)s', handlers=[logging.StreamHandler()])
+logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s', handlers=[logging.StreamHandler()])
 from cv_processor import process
 
 from pydantic import BaseModel
@@ -16,6 +16,30 @@ class Item(BaseModel):
 
 app = FastAPI()
 
+# Define the NiceGUI UI components
+@ui.page("/")
+def main_page():
+    async def handle_upload(e: events.UploadEventArguments) -> None:
+        ui.notify('Processing...')
+        # Read content -> image
+        nparr = np.frombuffer(e.content.read(), np.uint8)
+        img_np_bgr = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+        # Async process
+        results = await run.io_bound(process, img_np_bgr)
+
+        # Display
+        with ui.dialog() as dialog:
+            # Encode
+            retval, buffer = cv2.imencode('.png', results.get("image"))
+            img_buffer_encoded = base64.b64encode(buffer).decode('utf-8')
+            img_encoded = "data:image/png;base64,{}".format(img_buffer_encoded)
+            content = ui.image(img_encoded).props('fit=scale-down')
+        dialog.open()
+
+    ui.upload(on_upload=handle_upload, auto_upload=True, on_rejected=lambda: ui.notify('Rejected!')).props('accept=image').classes('max-w-full')
+
+ui.run_with(app, title="CV")
+
 @app.post('/process')
 def process_image(item: Item):
     logging.info("POST /process")
@@ -50,29 +74,3 @@ def process_image(item: Item):
     except Exception as e:
         logging.warning("Exception: {}".format(traceback.format_exc()))
         return {"error": traceback.format_exc()}
-
-# Define the NiceGUI UI components
-@ui.page("/")
-def main_page():
-
-    async def handle_upload(e: events.UploadEventArguments) -> None:
-        ui.notify('Processing...')
-        # Read content -> image
-        nparr = np.frombuffer(e.content.read(), np.uint8)
-        img_np_bgr = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-        # Async process
-        results = await run.io_bound(process, img_np_bgr)
-
-        # Display
-        with ui.dialog() as dialog:
-            # Encode
-            retval, buffer = cv2.imencode('.png', results.get("image"))
-            img_buffer_encoded = base64.b64encode(buffer).decode('utf-8')
-            img_encoded = "data:image/png;base64,{}".format(img_buffer_encoded)
-            content = ui.image(img_encoded).props('fit=scale-down')
-        dialog.open()
-
-    ui.upload(on_upload=handle_upload, auto_upload=True, on_rejected=lambda: ui.notify('Rejected!')).props('accept=image').classes('max-w-full')
-
-if __name__ == '__main__':
-    ui.run_with(app, title="CV")

app_cv/cv_processor.py

@@ -1,7 +1,7 @@
 import cv2
 import numpy as np
 import logging
-logging.basicConfig(level=logging.DEBUG, format='%(asctime)s [%(levelname)s] %(message)s', handlers=[logging.StreamHandler()])
+logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s', handlers=[logging.StreamHandler()])
 
 # Age
 from mivolo.predictor import Predictor