Fix ngrok bug on Colab

README.md

@@ -67,6 +67,7 @@ food-detection-yolov5
 
 
 <details open> <summary><strong>Dev logs</strong></summary>
+<strong><i>[01/05/2024]</i></strong>  Fix ngrok bug on Colab (migrate to pyngrok)<br>
 <strong><i>[24/10/2023]</i></strong>  Clean and refactor repo. Integrate YOLOv8 to food detection.<br>
 <strong><i>[07/03/2022]</i></strong>  Big refactor. Integrate object detection, image classification, semantic segmentation into one <b><i>Ship of Theseus</i></b>.<br>
 <strong><i>[31/01/2022]</i></strong>  Update to new YOLOv5 latest versions P5-P6. Can load checkpoints from original repo.<br>

app.py

@@ -1,57 +1,48 @@
 import os
+import threading
 import argparse
+import getpass
 
-from flask import Flask
 from flask_cors import CORS
-from flask_ngrok import run_with_ngrok
+from flask import Flask
+from pyngrok import ngrok, conf
 
 from backend.routes import set_routes
 from backend.constants import UPLOAD_FOLDER, CSV_FOLDER, DETECTION_FOLDER, SEGMENTATION_FOLDER, METADATA_FOLDER
 
 parser = argparse.ArgumentParser('Online Food Recognition')
 parser.add_argument('--ngrok', action='store_true',
                     default=False, help="Run on local or ngrok")
-parser.add_argument('--host',  type=str,
-                    default='localhost:8000', help="Local IP")
+parser.add_argument('--host', type=str, default='localhost', help="Local IP")
+parser.add_argument('--port', type=int, default=5000, help="Local port")
 parser.add_argument('--debug', action='store_true',
                     default=False, help="Run app in debug mode")
 
-
-app = Flask(__name__, template_folder='templates', static_folder='static')
-CORS(app, resources={r"/api/*": {"origins": "*"}})
-
-app.config['SEND_FILE_MAX_AGE_DEFAULT'] = 1
-app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
-app.config['CSV_FOLDER'] = CSV_FOLDER
-app.config['DETECTION_FOLDER'] = DETECTION_FOLDER
-app.config['SEGMENTATION_FOLDER'] = SEGMENTATION_FOLDER
-
-set_routes(app)
+args = parser.parse_args()
 
 if __name__ == '__main__':
-    if not os.path.exists(UPLOAD_FOLDER):
-        os.makedirs(UPLOAD_FOLDER, exist_ok=True)
-    if not os.path.exists(DETECTION_FOLDER):
-        os.makedirs(DETECTION_FOLDER, exist_ok=True)
-    if not os.path.exists(SEGMENTATION_FOLDER):
-        os.makedirs(SEGMENTATION_FOLDER, exist_ok=True)
-    if not os.path.exists(CSV_FOLDER):
-        os.makedirs(CSV_FOLDER, exist_ok=True)
-    if not os.path.exists(METADATA_FOLDER):
-        os.makedirs(METADATA_FOLDER, exist_ok=True)
-
-    args = parser.parse_args()
+    app = Flask(__name__, template_folder='templates', static_folder='static')
+
+    CORS(app, resources={r"/api/*": {"origins": "*"}})
+    app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
+    app.config['CSV_FOLDER'] = CSV_FOLDER
+    app.config['DETECTION_FOLDER'] = DETECTION_FOLDER
+    app.config['SEGMENTATION_FOLDER'] = SEGMENTATION_FOLDER
 
     if args.ngrok:
-        run_with_ngrok(app)
-        app.run()
+        print("Enter your authtoken, which can be copied from https://dashboard.ngrok.com/get-started/your-authtoken")
+        conf.get_default().auth_token = getpass.getpass()
+        public_url = ngrok.connect(args.port).public_url
+        print(
+            f" * ngrok tunnel \"{public_url}\" -> \"http://127.0.0.1:{args.port}/\"")
+        app.config['BASE_URL'] = public_url
     else:
-        hostname = str.split(args.host, ':')
-        if len(hostname) == 1:
-            port = 4000
-        else:
-            port = hostname[1]
-        host = hostname[0]
-
-        app.run(host=host, port=port, debug=args.debug, use_reloader=False,
-                ssl_context='adhoc')
+        app.config['BASE_URL'] = f"http://{args.host}:{args.port}"
+
+    set_routes(app)
+
+    for folder in [UPLOAD_FOLDER, DETECTION_FOLDER, SEGMENTATION_FOLDER, CSV_FOLDER, METADATA_FOLDER]:
+        os.makedirs(folder, exist_ok=True)
+
+    threading.Thread(target=app.run, kwargs={
+        "host": args.host, "port": args.port, "debug": args.debug, "use_reloader": False}).start()

requirements.txt

@@ -10,7 +10,7 @@ omegaconf
 pycocotools
 gdown>=4.4.0
 flask-cors
-flask_ngrok
+pyngrok
 cryptography
 tabulate
 segmentation-models-pytorch

theseus/utilities/visualization/utils.py

@@ -11,7 +11,7 @@ def draw_mask(polygons, mask_img):
 
 def draw_polylines(image, polygons):
     image = cv2.polylines(
-        image, [np.array(polygons, dtype=np.int)], True, (0, 0, 1), 2)
+        image, [np.array(polygons, dtype=int)], True, (0, 0, 1), 2)
     return image
 
 
@@ -136,15 +136,15 @@ def plot_one_box(img, box, key=None, value=None, color=None, line_thickness=None
                         thickness=tf, lineType=cv2.FONT_HERSHEY_SIMPLEX)
 
     # boxes input is xywh
-    boxes = np.array(boxes, np.int)
+    boxes = np.array(boxes, int)
     img_bgr = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
 
     for idx, (box, label_id, score) in enumerate(zip(boxes, label_ids, scores)):
         if label_names is not None:
             label = label_names[idx]
         if obj_list is not None:
             label = obj_list[label_id]
-        
+
         new_color = tuple(i*255.0 for i in color_list[int(label_id)])
 
         plot_one_box(

theseus/utilities/visualization/visualizer.py

@@ -124,7 +124,7 @@ def draw_polygon_ocr(self, polygons, texts=None, font='assets/fonts/aachenb.ttf'
 
         # Reduce opacity of original image
         o_image = reduce_opacity(image)
-        i_masked = (np.bitwise_not(mask)/255).astype(np.int)
+        i_masked = (np.bitwise_not(mask)/255).astype(int)
         o_image = o_image * i_masked
 
         # Add two image