add sorter and improve detections

.gitignore

@@ -1 +1,3 @@
-.idea
+.idea
+plates
+flagged

app.py

@@ -2,7 +2,8 @@ import gradio as gr
 import numpy as np
 import cv2
 from norfair import Detection, Tracker, Video
-from detector.utils import detect_plates, detect_chars, imcrop
+from detector.utils import detect_plates, detect_chars, imcrop, send_request, draw_text
+from threading import Thread
 
 DISTANCE_THRESHOLD_BBOX: float = 0.7
 DISTANCE_THRESHOLD_CENTROID: int = 30
@@ -31,15 +32,17 @@ def yolo_to_norfair(yolo_detections):
 
 
 def fn_image(foto):
-    plates = detect_plates(foto)
     plates_text = []
-    if len(plates) > 0:
-        for plate in plates:
-            p1, p2, crop = plate
+    plates = detect_plates(foto)
+    records = plates.pandas().xyxy[0].to_dict(orient='records')
+    if records:
+        for plate in records:
+            xi, yi, xf, yf = int(plate['xmin']), int(plate['ymin']), int(plate['xmax']), int(plate['ymax'])
+            crop = imcrop(foto, (xi, yi, xf, yf))
             if len(crop) > 0:
-                cv2.rectangle(foto, p1, p2, (0, 0, 255), 2)
-                text, crop = detect_chars(crop)
-                cv2.putText(foto, text, p1, cv2.FONT_HERSHEY_SIMPLEX, 4, (0, 255, 0), 5)
+                cv2.rectangle(foto, (xi, yi), (xf, yf), (0, 255, 0), 2)
+                text = detect_chars(crop)
+                draw_text(foto, text, (xi, yi))
                 plates_text.append(text)
     return foto, plates_text
 
@@ -62,12 +65,10 @@ def fn_video(video, initial_time, duration):
             ret, frame = cap.read()
             if not ret:
                 break
+            frame_copy = frame.copy()
         except Exception as e:
             print(e)
             continue
-        # num_frames += 1
-        # if num_frames % 3 != 0:
-        #     continue
         if num_frames < min_frame:
             num_frames += 1
             continue
@@ -82,6 +83,8 @@ def fn_video(video, initial_time, duration):
                     crop = imcrop(frame, bbox)
                     text = detect_chars(crop)
                     plates[obj.id] = text
+                    thread = Thread(target=send_request, args=(frame_copy, text, bbox))
+                    thread.start()
 
                 cv2.rectangle(
                     frame,
@@ -90,6 +93,7 @@ def fn_video(video, initial_time, duration):
                     (0, 255, 0),
                     2,
                 )
+                draw_text(frame, plates[obj.id], (bbox[0], bbox[1]))
                 cv2.putText(
                     frame,
                     plates[obj.id],

detector/utils.py

@@ -2,6 +2,9 @@ import torch
 import numpy as np
 import cv2
 import os
+from datetime import datetime
+from json import dumps
+import requests
 
 BASE_DIR = os.path.abspath(os.getcwd())
 
@@ -42,3 +45,44 @@ def detect_chars(img):
         records = sorted(records, key=lambda d: d['xmin'])
         text = ''.join([i.get('name') for i in records])
     return text
+
+
+def draw_text(img, text,
+              pos=(0, 0),
+              font_scale=1,
+              font_thickness=2,
+              text_color=(0, 255, 0),
+              text_color_bg=(0, 0, 0)
+              ):
+    x, y = pos
+    text_size, _ = cv2.getTextSize(text, 0, font_scale, font_thickness)
+    text_w, text_h = text_size
+    cv2.rectangle(img, pos, (x + text_w, y - text_h), text_color_bg, -1)
+    cv2.putText(img, text, (x, y), 0, font_scale, text_color, font_thickness)
+
+
+def send_request(frame, text, bbox):
+    cv2.rectangle(
+        frame,
+        (bbox[0], bbox[1]),
+        (bbox[2], bbox[3]),
+        (0, 255, 0),
+        2,
+    )
+    draw_text(frame, text, (bbox[0], bbox[1]))
+    url = "https://api.prevantec.com/toll-plates"
+    data = {
+        "number": text,
+        "camera": "camera_1",
+        "spot_on": str(datetime.now()),
+    }
+    if not os.path.exists(os.path.join(BASE_DIR, 'plates')):
+        os.makedirs(os.path.join(BASE_DIR, 'plates'))
+    filename = os.path.join(BASE_DIR, 'plates', f'{text}.jpg')
+    cv2.imwrite(filename, frame)
+    payload = {'data': dumps(data)}
+    files = [
+        ('files', (f'{text}.jpg', open(filename, 'rb'), 'image/jpg'))
+    ]
+    headers = {}
+    requests.request("POST", url, headers=headers, data=payload, files=files)