maintain yolov5 code

app.py

@@ -38,8 +38,8 @@ def inference(image, model_name, conf_threshold, iou_threshold):
     if model_name == "YOLO-V7":
         return get_yolov7_result(image, conf_threshold, iou_threshold, label_names)
     elif model_name == "YOLO-V5":
-        return get_yolov5_result(image, conf_threshold, iou_threshold, label_names)
-        #return None, None
+        #return get_yolov5_result(image, conf_threshold, iou_threshold, label_names)
+        return None, None
     elif model_name == "YOLO-V8":
         return get_yolov8_result(image, conf_threshold, iou_threshold, label_names)
     else:

infer/yolov5/get_results.py

@@ -4,12 +4,26 @@ import numpy as np
 import streamlit as st
 import os
 import shutil
+import sys
+import platform
 
 from infer.yolov5 import detect
 
 colors = [(np.random.randint(0, 255), np.random.randint(0, 255), np.random.randint(0, 255)) for _ in range(20)]
 
 def get_yolov5_result(image, conf_threshold, iou_threshold, class_names):
+
+    os_name = platform.system()
+    if os_name == 'Windows':
+        sys.path.insert(0, "infer\yolov5")
+    elif os_name == 'Linux':
+        sys.path.insert(0, "/home/user/app/infer/yolov5")
+    else:
+        return "Unknown"
+
+    if os.path.exists('temp/'):
+        shutil.rmtree('temp/', ignore_errors=True)
+
     weights = 'my_model/v5-n.pt'
     device = 'cpu'
     #model = torch.hub.load('ultralytics/yolov5', 'custom', path=weights, force_reload=True)
@@ -45,6 +59,7 @@ def get_yolov5_result(image, conf_threshold, iou_threshold, class_names):
     #
 
     result_list = []
+
     with open('temp/labels/temp.txt', "r") as f:
         lines = f.readlines()
         for line in lines:
@@ -73,6 +88,16 @@ def get_yolov5_result(image, conf_threshold, iou_threshold, class_names):
 
     remove_yolov5_temp_folders()
 
+    os_name = platform.system()
+    if os_name == 'Windows':
+        if "infer\yolov5" in sys.path:
+            sys.path.remove("infer\yolov5")
+    elif os_name == 'Linux':
+        if "/home/user/app/infer/yolov5" in sys.path:
+            sys.path.remove("/home/user/app/infer/yolov5")
+    else:
+        return "Unknown"
+
     return img0, result_list
 
 def remove_yolov5_temp_folders():

infer/yolov5/models/common.py

@@ -348,6 +348,17 @@ class DetectMultiBackend(nn.Module):
             w = attempt_download(w)  # download if not local
 
         if pt:  # PyTorch
+
+            import platform
+            import sys
+            os_name = platform.system()
+            if os_name == 'Windows':
+                sys.path.insert(0, "infer\yolov5")
+            elif os_name == 'Linux':
+                sys.path.insert(0, "/home/user/app/infer/yolov5")
+            else:
+                return "Unknown"
+
             model = attempt_load(weights if isinstance(weights, list) else w, device=device, inplace=True, fuse=fuse)
             stride = max(int(model.stride.max()), 32)  # model stride
             names = model.module.names if hasattr(model, 'module') else model.names  # get class names

infer/yolov5/models/experimental.py

@@ -72,7 +72,7 @@ class Ensemble(nn.ModuleList):
 
 def attempt_load(weights, device=None, inplace=True, fuse=True):
     # Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a
-    from models.yolo import Detect, Model
+    from infer.yolov5.models.yolo import Detect, Model
 
     model = Ensemble()
     for w in weights if isinstance(weights, list) else [weights]:

infer/yolov5/models/tf.py

@@ -28,7 +28,7 @@ import torch.nn as nn
 from tensorflow import keras
 
 from infer.yolov5.models.common import (C3, SPP, SPPF, Bottleneck, BottleneckCSP, C3x, Concat, Conv, CrossConv, DWConv,
-                           DWConvTranspose2d, Focus, autopad)
+                                        DWConvTranspose2d, Focus, autopad)
 from infer.yolov5.models.experimental import MixConv2d, attempt_load
 from infer.yolov5.models.yolo import Detect, Segment
 from infer.yolov5.utils.activations import SiLU

infer/yolov7/get_results.py

@@ -7,6 +7,8 @@ from infer.yolov7.utils.torch_utils import select_device
 import numpy as np
 import os
 from huggingface_hub import Repository
+import sys
+import platform
 
 colors = [(np.random.randint(0, 255), np.random.randint(0, 255), np.random.randint(0, 255)) for _ in range(20)]
 
@@ -53,4 +55,17 @@ def get_yolov7_result(image, conf_threshold, iou_threshold, class_names):
                 cv2.rectangle(img0, (x1, y1), (x2, y2), color, 2)
                 cv2.putText(img0, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
     img0 = img0[...,::-1]
+
+    os_name = platform.system()
+    if os_name == 'Windows':
+        if "infer\yolov7" in sys.path:
+            sys.path.remove("infer\yolov7")
+            # print(sys.path)
+    elif os_name == 'Linux':
+        if "/home/user/app/infer/yolov7" in sys.path:
+            sys.path.remove("/home/user/app/infer/yolov7")
+    else:
+        return "Unknown"
+
+
     return img0, result_list

infer/yolov7/models/experimental.py

@@ -263,7 +263,7 @@ def attempt_load(weights, map_location=None):
             sys.path.insert(0, "/home/user/app/infer/yolov7")
         else:
             return "Unknown"
-
+        #print(sys.path)
         #sys.path.insert(0, "/home/user/app/infer/yolov7")
         ckpt = torch.load(w, map_location=map_location)  # load
         model.append(ckpt['ema' if ckpt.get('ema') else 'model'].float().fuse().eval())  # FP32 model