fix_of_versions_in_yolovdemo

L07/Yolov5_setup/yolov5_setup.ipynb

@@ -217,69 +217,34 @@
    "id": "510d57eb-399c-4704-90f3-a4efd4bd3a3e",
    "metadata": {},
    "source": [
-    "An now you can test out a demo of Yolov5 -- one that predicts on the image `Figs/zidane.jpg`.\n",
-    "\n",
-    "If succefull an output prediction image will be placed in the `temp.jpg/`:"
+    "An now you can test out a demo of Yolov5 -- one that predicts on the image `Figs/zidane.jpg`:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "cac6ad2d-5e41-4131-94e5-476b8ba41d91",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "VERSIONS:\n",
-      "  _sys.version                             = 3.9.7 (default, Sep 16 2021, 13:09:58) \n",
-      "[GCC 7.5.0]\n",
-      "  torch.__version__                        = 1.10.1+cu111\n",
-      "  torch.cuda.is_available()                = True\n",
-      "  torch.backends.cudnn.enabled             = True\n",
-      "  torch.cuda.get_device_properties(device) = _CudaDeviceProperties(name='NVIDIA GeForce GTX 1080', major=6, minor=1, total_memory=8119MB, multi_processor_count=20)\n",
-      "  torch.tensor([1.0, 2.0]).cuda()          = tensor([1., 2.], device='cuda:0')\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Using cache found in /home/cef/.cache/torch/hub/ultralytics_yolov5_master\n",
-      "YOLOv5 🚀 2022-1-11 torch 1.10.1+cu111 CUDA:0 (NVIDIA GeForce GTX 1080, 8119MiB)\n",
-      "\n",
-      "Fusing layers... \n",
-      "Model Summary: 213 layers, 7225885 parameters, 0 gradients, 16.5 GFLOPs\n",
-      "Adding AutoShape... \n",
-      "image 1/1: 720x1280 2 persons, 2 ties\n",
-      "Speed: 132.4ms pre-process, 16.4ms inference, 28.6ms NMS per image at shape (1, 3, 384, 640)\n",
-      "Saved 1 image to \u001b[1mtemp.jpg\u001b[0m\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "OK\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "#!/usr/bin/env python3\n",
     "\n",
     "import torch\n",
     "import sys\n",
-    "\n",
+    "    \n",
     "def Versions():\n",
     "    print(\"VERSIONS:\")\n",
-    "    print(f\"  _sys.version                             = { sys.version}\")\n",
+    "    print(f\"  sys.version                              = {sys.version}\")\n",
     "    print(f\"  torch.__version__                        = {torch.__version__}\")\n",
-    "    print(f\"  torch.cuda.is_available()                = {torch.cuda.is_available()}\")\n",
-    "    print(f\"  torch.backends.cudnn.enabled             = {torch.backends.cudnn.enabled}\")\n",
-    "    device = torch.device(\"cuda\")\n",
-    "    print(f\"  torch.cuda.get_device_properties(device) = {torch.cuda.get_device_properties(device)}\")\n",
-    "    print(f\"  torch.tensor([1.0, 2.0]).cuda()          = {torch.tensor([1.0, 2.0]).cuda()}\")\n",
+    "   \n",
+    "    hasCuda = torch.cuda.is_available()\n",
+    "    print(f\"  torch.cuda.is_available()                = {hasCuda}\")\n",
+    "    if hasCuda:\n",
+    "        print(f\"  torch.backends.cudnn.enabled             = {torch.backends.cudnn.enabled}\")\n",
+    "        device = torch.device(\"cuda\")\n",
+    "        print(f\"  torch.cuda.get_device_properties(device) = {torch.cuda.get_device_properties(device)}\")\n",
+    "        print(f\"  torch.tensor([1.0, 2.0]).cuda()          = {torch.tensor([1.0, 2.0]).cuda()}\")\n",
+    "        \n",
     "\n",
     "def PredictDemo():\n",
     "    # Model\n",
@@ -303,6 +268,31 @@
     "print(\"OK\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "2211aee5",
+   "metadata": {},
+   "source": [
+    "If succefull an output prediction image will be placed in the temp.jpg/ or in runs/detect/expNN so look for the output line from the cell, similar to\n",
+    "\n",
+    "```\n",
+    "VERSIONS:\n",
+    "  sys.version                              = 3.9.7 ...\n",
+    "  torch.__version__                        = 1.11.0+cpu\n",
+    "  torch.cuda.is_available()                = False\n",
+    "\n",
+    "Using cache found in C:\\Users\\au204573/.cache\\torch\\hub\\ultralytics_yolov5_master\n",
+    "YOLOv5  2022-4-3 torch 1.11.0+cpu CPU\n",
+    "\n",
+    "Fusing layers... \n",
+    "YOLOv5s summary: 213 layers, 7225885 parameters, 0 gradients\n",
+    "Adding AutoShape... \n",
+    "image 1/1: 720x1280 2 persons, 2 ties\n",
+    "Speed: 31.6ms pre-process, 298.2ms inference, 2.2ms NMS per image at shape (1, 3, 384, 640)\n",
+    "Saved 1 image to temp.jpg\n",
+    "```"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 24,
@@ -334,6 +324,8 @@
     "    plt.xticks([]), plt.yticks([])  # Hides the graph ticks and x / y axis\n",
     "    plt.show()\n",
     "    \n",
+    "\n",
+    "#ShowImg('runs/detect/exp2/zidane.jpg')\n",
     "ShowImg('temp.jpg/zidane.jpg')"
    ]
   }
@@ -354,7 +346,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.11"
   }
  },
  "nbformat": 4,