v03 update

app.py

@@ -43,6 +43,9 @@ suffix_list = [".csv", ".yaml"]
 # font size
 FONTSIZE = 25
 
+# object style
+obj_style = ["Small Object", "Medium Object", "Large Object"]
+
 
 def parse_args(known=False):
     parser = argparse.ArgumentParser(description="Gradio YOLOv5 Det v0.3")
@@ -168,6 +171,11 @@ def yolo_det(img, device, model_name, inference_size, conf, iou, max_num, model_
 
     global model, model_name_tmp, device_tmp
 
+    # object size num
+    s_obj, m_obj, l_obj = 0, 0, 0
+    # object area list
+    area_obj_all = []
+
     if model_name_tmp != model_name:
         # Model judgment to avoid repeated loading
         model_name_tmp = model_name
@@ -232,10 +240,16 @@ def yolo_det(img, device, model_name, inference_size, conf, iou, max_num, model_
                 opt,
             )
 
-    det_json = export_json(results, model, img.size)[0] # Detection information
+            # ----------add object size----------
+            w_obj = x1 - x0
+            h_obj = y1 - y0
+            area_obj = w_obj * h_obj
+            area_obj_all.append(area_obj)
 
-    # JSON formatting
-    det_json_format = json.dumps(det_json, sort_keys=False, indent=4, separators=(",", ":"), ensure_ascii=False)
+    det_json = export_json(results, model, img.size)[0] # Detection information
+    det_json_format = json.dumps(det_json, sort_keys=False, indent=4, separators=(",", ":"), ensure_ascii=False) # JSON formatting
+    if "json" not in opt:
+        det_json = None
 
     # -------pdf-------
     report = "./Det_Report.pdf"
@@ -244,10 +258,20 @@ def yolo_det(img, device, model_name, inference_size, conf, iou, max_num, model_
     else:
         report = None
 
-    if "json" not in opt:
-        det_json = None
+    # --------------object size compute--------------
+    for i in range(len(area_obj_all)):
+        if (0 < area_obj_all[i] <= 32 ** 2):
+            s_obj = s_obj + 1
+        elif (32 ** 2 < area_obj_all[i] <= 96 ** 2):
+            m_obj = m_obj + 1
+        elif (area_obj_all[i] > 96 ** 2):
+            l_obj = l_obj + 1
+
+    sml_obj_total = s_obj + m_obj + l_obj
+
+    objSize_dict = {obj_style[i]: [s_obj, m_obj, l_obj][i] / sml_obj_total for i in range(3)}
 
-    return det_img, det_json, report, dataframe
+    return det_img, det_json, report, dataframe, objSize_dict
 
 
 def main(args):
@@ -311,8 +335,9 @@ def main(args):
     outputs_json = gr.outputs.JSON(label="Detection information")
     outputs_pdf = gr.outputs.File(label="Download test report")
     outputs_df = gr.outputs.Dataframe(max_rows=5, overflow_row_behaviour="paginate", type="pandas", label="List of detection information")
+    outputs_objSize = gr.outputs.Label(label="Object size ratio statistics")
 
-    outputs = [outputs_img, outputs_json, outputs_pdf, outputs_df]
+    outputs = [outputs_img, outputs_json, outputs_pdf, outputs_df, outputs_objSize]
 
     # title
     title = "Gradio YOLOv5 Det v0.3"