Update app.py

app.py

@@ -1,8 +1,9 @@
-# Gradio YOLOv8 Det v0.2.4
+# Gradio YOLOv8 Det v0.2.5
 # 创建人：曾逸夫
-# 创建时间：2023-08-14
+# 创建时间：2023-10-21
 
 import argparse
+import csv
 import gc
 import json
 import os
@@ -44,7 +45,7 @@ from util.fonts_opt import is_fonts
 ROOT_PATH = sys.path[0]  # 根目录
 
 # Gradio YOLOv8 Det版本
-GYD_VERSION = "Gradio YOLOv8 Det v0.2.3"
+GYD_VERSION = "Gradio YOLOv8 Det v0.2.5"
 
 # 文件后缀
 suffix_list = [".csv", ".yaml"]
@@ -57,7 +58,7 @@ obj_style = ["小目标", "中目标", "大目标"]
 
 
 def parse_args(known=False):
-    parser = argparse.ArgumentParser(description="Gradio YOLOv8 Det v0.2.3")
+    parser = argparse.ArgumentParser(description="Gradio YOLOv8 Det v0.2.5")
     parser.add_argument("--model_type", "-mt", default="online", type=str, help="model type")
     parser.add_argument("--source", "-src", default="upload", type=str, help="image input source")
     parser.add_argument("--source_video", "-src_v", default="upload", type=str, help="video input source")
@@ -240,13 +241,14 @@ def seg_output(img_path, seg_mask_list, color_list, cls_list):
     img = cv2.imread(img_path)
     img_c = img.copy()
 
-    w, h = img.shape[1], img.shape[0]
+    # w, h = img.shape[1], img.shape[0]
 
     # 获取分割坐标
     for seg_mask, cls_index in zip(seg_mask_list, cls_list):
         img_mask = []
         for i in range(len(seg_mask)):
-            img_mask.append([seg_mask[i][0] * w, seg_mask[i][1] * h])
+            # img_mask.append([seg_mask[i][0] * w, seg_mask[i][1] * h])
+            img_mask.append([seg_mask[i][0], seg_mask[i][1]])
 
         polygon_drawing(img_mask, img_c, color_list[int(cls_index)])  # 绘制分割图形
 
@@ -255,7 +257,7 @@ def seg_output(img_path, seg_mask_list, color_list, cls_list):
     return img_mask_merge
 
 
-# YOLOv5图片检测函数
+# YOLOv8图片检测函数
 def yolo_det_img(img_path, model_name, infer_size, conf, iou):
 
     global model, model_name_tmp, device_tmp
@@ -281,7 +283,8 @@ def yolo_det_img(img_path, model_name, infer_size, conf, iou):
 
     # 图像分割
     if (model_name[-3:] == "seg"):
-        masks_list = predict_results.masks.segments
+        # masks_list = predict_results.masks.xyn
+        masks_list = predict_results.masks.xy
         img_mask_merge = seg_output(img_path, masks_list, color_list, cls_list)
         img = Image.fromarray(cv2.cvtColor(img_mask_merge, cv2.COLOR_BGRA2RGBA))
     else: