CV app with fastapi, web nicegui based

app_cv/Dockerfile

@@ -0,0 +1,28 @@
+FROM python:3.12
+
+WORKDIR /app
+
+# LibGL for OpenCV
+RUN apt-get update && apt-get install libgl1 -y
+
+# Download models
+RUN mkdir models
+
+# https://github.com/wildchlamydia/mivolo
+RUN curl "https://drive.usercontent.google.com/download?id=11i8pKctxz3wVkDBlWKvhYIh7kpVFXSZ4&confirm=xxx" -o models/model_imdb_cross_person_4.22_99.46.pth.tar
+RUN curl "https://drive.usercontent.google.com/download?id=1CGNCkZQNj5WkP3rLpENWAOgrBQkUWRdw&confirm=xxx" -o models/yolov8x_person_face.pt
+
+# https://github.com/notAI-tech/NudeNet
+# Upload to an accessible link: https://github.com/notAI-tech/NudeNet/releases/download/v3.4-weights/640m.onnx
+RUN curl "https://drive.usercontent.google.com/download?id=1lHTrW1rmYoYnMSUlhLwqFCW61-w2hvKX&confirm=xxx" -o models/640m.onnx
+
+COPY . .
+RUN pip install --no-cache-dir -r requirements.txt
+
+EXPOSE 5000
+
+# CMD ["gunicorn", "--bind", "0.0.0.0:5000", "--workers", "2", "app:app"]
+CMD ["uvicorn", "--port", "5000", "--workers", "2", "app:app"]
+
+# docker build -t fetcher_cv .
+# docker run --rm -p 5000:5000 fetcher_cv

app_cv/README.md

@@ -1,17 +0,0 @@
-# Requirements
-
-```
-pip install git+https://github.com/wildchlamydia/mivolo.git "nudenet>=3.4.2"
-```
-
-- Download checkpoints
-    - https://github.com/wildchlamydia/mivolo
-        - models/mivolo/model_imdb_cross_person_4.22_99.46.pth.tar
-        - models/mivolo/yolov8x_person_face.pt
-    - https://github.com/notAI-tech/NudeNet?tab=readme-ov-file#available-models
-        - models/nude_detector/640m.onnx
-
-
-# TODO
-
-- Client side inference: https://github.com/notAI-tech/NudeNet/tree/v3/in_browser

app_cv/app.py

@@ -1,33 +1,41 @@
-from flask import Flask, request, jsonify
+from fastapi import FastAPI
+from nicegui import ui, events, run
 import base64
 import io
+import numpy as np
 import cv2
 import traceback
-import os
 import logging
 logging.basicConfig(level=logging.DEBUG, format='%(asctime)s [%(levelname)s] %(message)s', handlers=[logging.StreamHandler()])
 from cv_processor import process
 
-app = Flask(__name__)
+from pydantic import BaseModel
 
-@app.route('/process', methods=['POST'])
+class Item(BaseModel):
-def process_image():
+    image: str # Base64
+
+app = FastAPI()
+
+@app.post('/process')
+def process_image(item: Item):
     logging.info("POST /process")
-    # Json
-    data = request.get_json()
-    # Valid data?
-    if not data or 'image' not in data:
-        return jsonify({"error": "No image data provided"}), 400
-
     try:
-        image_data = data['image']
+        image_data = item.image
+        if (image_data is None):
+            return {"error": "No image data provided"}
 
         # Decode base64 string
         image_bytes = base64.b64decode(image_data)
         image_stream = io.BytesIO(image_bytes)
+        # Convert bytes to NumPy array
+        img_array = np.frombuffer(image_stream.getvalue(), dtype=np.uint8)
+        # Decode image using OpenCV
+        img_bgr = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
+        # Valid image
+        assert(img_bgr is not None)
 
         # Process the image
-        results = process(image_stream)
+        results = process(img_bgr)
 
         # Encode processed image to base64
         _, buffer = cv2.imencode('.jpg', results.get("image"), [cv2.IMWRITE_JPEG_QUALITY, 100])
@@ -37,12 +45,34 @@ def process_image():
         results["image_b64"] = processed_image_base64
         # Pop image (not serializable)
         results.pop("image")
-        # Jsonify
+        return results
-        return jsonify(results)
     
     except Exception as e:
         logging.warning("Exception: {}".format(traceback.format_exc()))
-        return jsonify({"error": traceback.format_exc()}), 400
+        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__':
-    app.run(debug=os.getenv("DEBUG_MODE", False))
+    ui.run_with(app, title="CV")

app_cv/cv_processor.py

@@ -14,8 +14,8 @@ class CV():
     def __init__(self):
         args = argparse.ArgumentParser()
         args.add_argument("--device", type=str, default="cpu")
-        args.add_argument("--checkpoint", default="models/mivolo/model_imdb_cross_person_4.22_99.46.pth.tar")
+        args.add_argument("--checkpoint", default="models/model_imdb_cross_person_4.22_99.46.pth.tar")
-        args.add_argument("--detector_weights", default="models/mivolo/yolov8x_person_face.pt")
+        args.add_argument("--detector_weights", default="models/yolov8x_person_face.pt")
         args.add_argument("--with-persons", action="store_true", default=False, help="If set model will run with persons, if available")
         args.add_argument("--disable-faces", action="store_true", default=False, help="If set model will use only persons if available")
         args.add_argument("--draw", action="store_true", default=False, help="If set, resulted images will be drawn")
@@ -24,7 +24,7 @@ class CV():
         self.predictor_age = Predictor(args)
 
         # Initialize
-        self.nude_detector = NudeDetector(model_path="models/nude_detector/640m.onnx", inference_resolution=640)
+        self.nude_detector = NudeDetector(model_path="models/640m.onnx", inference_resolution=640)
         # detector = NudeDetector(model_path="downloaded_640m.onnx path", inference_resolution=640)
         # https://github.com/notAI-tech/NudeNet?tab=readme-ov-file#available-models
 
@@ -112,16 +112,9 @@ class CV():
         }
         return results
 
-def process(image_bytes):
+def process(img_bgr):
     try:
         logging.info("Processing image")
-        # Convert bytes to NumPy array
-        img_array = np.frombuffer(image_bytes.getvalue(), dtype=np.uint8)
-        # Decode image using OpenCV
-        img_bgr = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
-
-        if img_bgr is None:
-            return {}
         # Process
         results = CV().process_image(img_bgr)
         logging.info("Returning results")

app_cv/docker-compose.yml

@@ -0,0 +1,19 @@
+services:
+  matitos_cv:
+    build:
+      context: .
+    image: fetcher_app_cv
+    container_name: fetcher_app_cv
+    restart: unless-stopped
+    ports:
+      - 5000
+    environment:
+      - DEBUG_MODE=0
+    labels:  # Reverse proxy sample
+      - "traefik.enable=true"
+      - "traefik.http.routers.cv.rule=Host(`cv.matitos.org`)"
+      - "traefik.http.routers.cv.entrypoints=websecure"
+      - "traefik.http.routers.cv.tls.certresolver=myresolvercd"
+      - "traefik.http.services.cv.loadbalancer.server.port=5000"
+    networks:
+      - docker_default  # Reverse proxy network

app_cv/requirements.txt

@@ -0,0 +1,7 @@
+opencv-python
+git+https://github.com/wildchlamydia/mivolo.git
+nudenet>=3.4.2
+torch==2.5
+nicegui
+fastapi
+gunicorn

app_cv_face/ABC.ipynb

@@ -0,0 +1,55 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Warning: Binary output can mess up your terminal. Use \"--output -\" to tell \n",
+      "Warning: curl to output it to your terminal anyway, or consider \"--output \n",
+      "Warning: <FILE>\" to save to a file.\n"
+     ]
+    }
+   ],
+   "source": [
+    "!curl https://api.missingkids.org/photographs/NCMC2049364c1.jpg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# !pip install deepface\n",
+    "# !pip install tf-keras\n",
+    "from deepface import DeepFace"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "matitos_cv_face",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}