added detection counts

.streamlit/config.toml

@@ -0,0 +1,6 @@
+[theme]
+primaryColor="#F63366"
+backgroundColor="#FFFFFF"
+secondaryBackgroundColor="#F0F2F6"
+textColor="#262730"
+font="sans serif"

app.py

@@ -37,6 +37,8 @@ def run_inference(model, img_paths):
 # helper function to process result and return image with bbox overlays
 def process_inference_result(result, class_colors):
 
+  # setup label counts
+  label_counts = {'class': [], 'count': []}
   # extract result objects
   img = result.orig_img
   dh, dw, _ = img.shape
@@ -55,10 +57,25 @@ def process_inference_result(result, class_colors):
     voc_y1 = voc_box[1]
     voc_x2 = voc_box[2]
     voc_y2 = voc_box[3]
+    class_name = aircraft_lookup[classes[labels[i]]]
     cv2.rectangle(img, (voc_x1, voc_y1), (voc_x2, voc_y2), class_colors[labels[i]], 2)
-    cv2.putText(img, aircraft_lookup[classes[labels[i]]]  + ' ' + str(round(conf[i], 2)), (voc_x1, voc_y1-5), cv2.FONT_HERSHEY_SIMPLEX, 1, class_colors[labels[i]], 2)
-
-  return img
+    cv2.putText(img, class_name  + ' ' + str(round(conf[i], 2)), (voc_x1, voc_y1-5), cv2.FONT_HERSHEY_SIMPLEX, 1, class_colors[labels[i]], 2)
+    if class_name not in label_counts['class']:
+        label_counts['class'].append(class_name)
+        label_counts['count'].append(1)
+    else:
+        label_counts['count'][label_counts['class'].index(class_name)] += 1
+
+  return img, label_counts
+
+def get_detection_count_display(classes):
+  if(len(classes)): 
+    disp_str = "[Aircraft detected] "
+    for class_name, count in enumerate(classes):
+      disp_str += class_name + ": " + str(count) + "  " 
+  else:
+    disp_str = "[No aircraft detected]"
+  return disp_str
 
 def run_process_show(img_path):
   results = model(img_path)
@@ -107,7 +124,7 @@ big_img = st.image(img)
 status.write("Running OneEye detector...")
 
 # process image through detector
-img2 = run_process_show(img)
+img2, detection_labels = run_process_show(img)
 big_img.image(img2)
 
-status.write("[Aircraft detected] F-16: 5 ")
+status.write(get_detection_count_display(detection_labels))