Infinite wait - deepstream-test1

dp.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating a deepstream pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('../')\n",
    "import gi\n",
    "import configparser\n",
    "gi.require_version('Gst', '1.0')\n",
    "from gi.repository import GLib, Gst\n",
    "from ctypes import *\n",
    "import time\n",
    "import sys\n",
    "import math\n",
    "import platform\n",
    "from common.is_aarch_64 import is_aarch64\n",
    "from common.bus_call import bus_call\n",
    "from common.FPS import PERF_DATA\n",
    "\n",
    "import cv2\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gi\n",
    "\n",
    "perf_data = None\n",
    "\n",
    "MAX_DISPLAY_LEN=64\n",
    "\n",
    "PGIE_CLASS_ID_VEHICLE = 0\n",
    "PGIE_CLASS_ID_BICYCLE = 1\n",
    "PGIE_CLASS_ID_PERSON = 2\n",
    "PGIE_CLASS_ID_ROADSIGN = 3\n",
    "pgie_classes_str= [\"Vehicle\", \"TwoWheeler\", \"Person\",\"RoadSign\"]\n",
    "\n",
    "MUXER_OUTPUT_WIDTH=1920\n",
    "MUXER_OUTPUT_HEIGHT=1080\n",
    "MUXER_BATCH_TIMEOUT_USEC=4000000\n",
    "\n",
    "TILED_OUTPUT_WIDTH=1280\n",
    "TILED_OUTPUT_HEIGHT=720\n",
    "\n",
    "GST_CAPS_FEATURES_NVMM=\"memory:NVMM\"\n",
    "\n",
    "OSD_PROCESS_MODE= 0\n",
    "OSD_DISPLAY_TEXT= 1\n",
    "\n",
    "args = [\"testing.py\", \"/home/mher/projects/counter/sample_h264.mp4\", \"/home/mher/projects/counter/sample_pyout_h264.mp4\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from common.is_aarch_64 import is_aarch64\n",
    "from common.bus_call import bus_call\n",
    "from common.FPS import PERF_DATA\n",
    "\n",
    "PGIE_CLASS_ID_VEHICLE = 2\n",
    "PGIE_CLASS_ID_PERSON = 0\n",
    "TILED_OUTPUT_WIDTH = 1920\n",
    "TILED_OUTPUT_HEIGHT = 1080"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def osd_sink_pad_buffer_probe(pad,info,u_data):\n",
    "    frame_number=0\n",
    "    print(frame_number)\n",
    "    #Intiallizing object counter with 0.\n",
    "    obj_counter = {\n",
    "        PGIE_CLASS_ID_VEHICLE:0,\n",
    "        PGIE_CLASS_ID_PERSON:0,\n",
    "        PGIE_CLASS_ID_BICYCLE:0,\n",
    "        PGIE_CLASS_ID_ROADSIGN:0\n",
    "    }\n",
    "    num_rects=0\n",
    "\n",
    "    gst_buffer = info.get_buffer()\n",
    "    if not gst_buffer:\n",
    "        print(\"Unable to get GstBuffer \")\n",
    "        return\n",
    "\n",
    "    # Retrieve batch metadata from the gst_buffer\n",
    "    # Note that pyds.gst_buffer_get_nvds_batch_meta() expects the\n",
    "    # C address of gst_buffer as input, which is obtained with hash(gst_buffer)\n",
    "    batch_meta = pyds.gst_buffer_get_nvds_batch_meta(hash(gst_buffer))\n",
    "    l_frame = batch_meta.frame_meta_list\n",
    "    while l_frame is not None:\n",
    "        try:\n",
    "            # Note that l_frame.data needs a cast to pyds.NvDsFrameMeta\n",
    "            # The casting is done by pyds.glist_get_nvds_frame_meta()\n",
    "            # The casting also keeps ownership of the underlying memory\n",
    "            # in the C code, so the Python garbage collector will leave\n",
    "            # it alone.\n",
    "            #frame_meta = pyds.glist_get_nvds_frame_meta(l_frame.data)\n",
    "            frame_meta = pyds.NvDsFrameMeta.cast(l_frame.data)\n",
    "        except StopIteration:\n",
    "            break\n",
    "\n",
    "        frame_number=frame_meta.frame_num\n",
    "        num_rects = frame_meta.num_obj_meta\n",
    "        l_obj=frame_meta.obj_meta_list\n",
    "        while l_obj is not None:\n",
    "            try:\n",
    "                # Casting l_obj.data to pyds.NvDsObjectMeta\n",
    "                #obj_meta=pyds.glist_get_nvds_object_meta(l_obj.data)\n",
    "                obj_meta=pyds.NvDsObjectMeta.cast(l_obj.data)\n",
    "            except StopIteration:\n",
    "                break\n",
    "            obj_counter[obj_meta.class_id] += 1\n",
    "            obj_meta.rect_params.border_color.set(0.0, 0.0, 1.0, 0.0)\n",
    "            try: \n",
    "                l_obj=l_obj.next\n",
    "            except StopIteration:\n",
    "                break\n",
    "\n",
    "        # Acquiring a display meta object. The memory ownership remains in\n",
    "        # the C code so downstream plugins can still access it. Otherwise\n",
    "        # the garbage collector will claim it when this probe function exits.\n",
    "        display_meta=pyds.nvds_acquire_display_meta_from_pool(batch_meta)\n",
    "        display_meta.num_labels = 1\n",
    "        py_nvosd_text_params = display_meta.text_params[0]\n",
    "        # Setting display text to be shown on screen\n",
    "        # Note that the pyds module allocates a buffer for the string, and the\n",
    "        # memory will not be claimed by the garbage collector.\n",
    "        # Reading the display_text field here will return the C address of the\n",
    "        # allocated string. Use pyds.get_string() to get the string content.\n",
    "        py_nvosd_text_params.display_text = \"Frame Number={} Number of Objects={} Vehicle_count={} Person_count={}\".format(frame_number, num_rects, obj_counter[PGIE_CLASS_ID_VEHICLE], obj_counter[PGIE_CLASS_ID_PERSON])\n",
    "\n",
    "        # Now set the offsets where the string should appear\n",
    "        py_nvosd_text_params.x_offset = 10\n",
    "        py_nvosd_text_params.y_offset = 12\n",
    "\n",
    "        # Font , font-color and font-size\n",
    "        py_nvosd_text_params.font_params.font_name = \"Serif\"\n",
    "        py_nvosd_text_params.font_params.font_size = 10\n",
    "        # set(red, green, blue, alpha); set to White\n",
    "        py_nvosd_text_params.font_params.font_color.set(1.0, 1.0, 1.0, 1.0)\n",
    "\n",
    "        # Text background color\n",
    "        py_nvosd_text_params.set_bg_clr = 1\n",
    "        # set(red, green, blue, alpha); set to Black\n",
    "        py_nvosd_text_params.text_bg_clr.set(0.0, 0.0, 0.0, 1.0)\n",
    "        # Using pyds.get_string() to get display_text as string\n",
    "        print(pyds.get_string(py_nvosd_text_params.display_text))\n",
    "        pyds.nvds_add_display_meta_to_frame(frame_meta, display_meta)\n",
    "        try:\n",
    "            l_frame=l_frame.next\n",
    "        except StopIteration:\n",
    "            break\n",
    "\n",
    "    return Gst.PadProbeReturn.OK"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating Pipeline \n",
      " \n"
     ]
    }
   ],
   "source": [
    "# Standard GStreamer initialization\n",
    "Gst.init(None)\n",
    "\n",
    "# Create gstreamer elements\n",
    "# Create Pipeline element that will form a connection of other elements\n",
    "print(\"Creating Pipeline \\n \")\n",
    "pipeline = Gst.Pipeline()\n",
    "if not pipeline:\n",
    "        print(\" Unable to create Pipeline \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating Source \n",
      " \n"
     ]
    }
   ],
   "source": [
    "# Source element for reading from the file\n",
    "print(\"Creating Source \\n \")\n",
    "source = Gst.ElementFactory.make(\"filesrc\", \"file-source\")\n",
    "if not source:\n",
    "    print(\" Unable to create Source \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating H264Parser \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Since the data format in the input file is elementary h264 stream,\n",
    "# we need a h264parser\n",
    "print(\"Creating H264Parser \\n\")\n",
    "h264parser = Gst.ElementFactory.make(\"h264parse\", \"h264-parser\")\n",
    "if not h264parser:\n",
    "    print(\" Unable to create h264 parser \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating Decoder \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Use nvdec_h264 for hardware accelerated decode on GPU\n",
    "print(\"Creating Decoder \\n\")\n",
    "decoder = Gst.ElementFactory.make(\"nvv4l2decoder\", \"nvv4l2-decoder\")\n",
    "if not decoder:\n",
    "    print(\" Unable to create Nvv4l2 Decoder \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating Muxer \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Create nvstreammux instance to form batches from one or more sources.\n",
    "print(\"Creating Muxer \\n\")\n",
    "streammux = Gst.ElementFactory.make(\"nvstreammux\", \"Stream-muxer\")\n",
    "if not streammux:\n",
    "    print(\" Unable to create NvStreamMux \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating pgie\n"
     ]
    }
   ],
   "source": [
    "# Use nvinfer to run inferencing on decoder's output,\n",
    "# behaviour of inferencing is set through config file\n",
    "print(\"Creating pgie\")\n",
    "pgie = Gst.ElementFactory.make(\"nvinfer\", \"primary-inference\")\n",
    "if not pgie:\n",
    "    print(\" Unable to create pgie \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating nvvidconv\n"
     ]
    }
   ],
   "source": [
    "# Use convertor to convert from NV12 to RGBA as required by nvosd\n",
    "print(\"Creating nvvidconv\")\n",
    "nvvidconv = Gst.ElementFactory.make(\"nvvideoconvert\", \"convertor\")\n",
    "if not nvvidconv:\n",
    "    print(\" Unable to create nvvidconv \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating OSD\n"
     ]
    }
   ],
   "source": [
    "# Create OSD to draw on the converted RGBA buffer\n",
    "print(\"Creating OSD\")\n",
    "nvosd = Gst.ElementFactory.make(\"nvdsosd\", \"onscreendisplay\")\n",
    "if not nvosd:\n",
    "        print(\" Unable to create nvosd \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Finally render the osd output\n",
    "# if is_aarch64():\n",
    "#     transform = Gst.ElementFactory.make(\"nvegltransform\", \"nvegl-transform\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating File sink \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Creating File sink \\n\")\n",
    "sink = Gst.ElementFactory.make(\"filesink\", \"nvvideo-renderer\")\n",
    "if not sink:\n",
    "    print(\" Unable to create file sink \\n\")\n",
    "\n",
    "# print(\"Creating EGL sink \\n\")\n",
    "# sink = Gst.ElementFactory.make(\"nveglglessink\", \"nvvideo-renderer\")\n",
    "# if not sink:\n",
    "#     print(\" Unable to create egl sink \\n\")\n",
    "\n",
    "# print(\"Creating fake sink \\n\")\n",
    "# sink = Gst.ElementFactory.make(\"fakesink\", \"nvvideo-renderer\")\n",
    "# if not sink:\n",
    "#     print(\" Unable to create fake sink \\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Playing file /home/mher/projects/counter/sample_h264.mp4 \n",
      "Adding elements to Pipeline \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Playing file %s \" %args[1])\n",
    "source.set_property('location', args[1])\n",
    "sink.set_property(\"location\", args[2])\n",
    "streammux.set_property('width', 1920)\n",
    "streammux.set_property('height', 1080)\n",
    "streammux.set_property('batch-size', 1)\n",
    "streammux.set_property('batched-push-timeout', 4000000)\n",
    "pgie.set_property('config-file-path', \"/home/mher/projects/counter/deepstream-analytics/dsnvanalytics_pgie_config.txt\")\n",
    "\n",
    "\n",
    "print(\"Adding elements to Pipeline \\n\")\n",
    "pipeline.add(source)\n",
    "pipeline.add(h264parser)\n",
    "pipeline.add(decoder)\n",
    "pipeline.add(streammux)\n",
    "pipeline.add(pgie)\n",
    "pipeline.add(nvvidconv)\n",
    "# pipeline.add(nvosd)\n",
    "pipeline.add(sink)\n",
    "# if is_aarch64():\n",
    "#     pipeline.add(transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linking elements in the Pipeline \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we link the elements together\n",
    "# file-source -> h264-parser -> nvh264-decoder ->\n",
    "# nvinfer -> nvvidconv -> nvosd -> video-renderer\n",
    "print(\"Linking elements in the Pipeline \\n\")\n",
    "\n",
    "source.link(h264parser)\n",
    "h264parser.link(decoder)\n",
    "\n",
    "sinkpad = streammux.get_request_pad(\"sink_0\")\n",
    "if not sinkpad:\n",
    "    print(\" Unable to get the sink pad of streammux \\n\")\n",
    "    \n",
    "srcpad = decoder.get_static_pad(\"src\")\n",
    "if not srcpad:\n",
    "    print(\" Unable to get source pad of decoder \\n\")\n",
    "    \n",
    "srcpad.link(sinkpad)\n",
    "streammux.link(pgie)\n",
    "pgie.link(nvvidconv)\n",
    "\n",
    "nvvidconv.link(sink)\n",
    "# nvosd.link(sink)\n",
    "# nvvidconv.link(nvosd)\n",
    "# if is_aarch64():\n",
    "#     nvosd.link(transform)\n",
    "#     transform.link(sink)\n",
    "# else:\n",
    "#     nvosd.link(sink)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create an event loop and feed gstreamer bus mesages to it\n",
    "loop = GLib.MainLoop()\n",
    "bus = pipeline.get_bus()\n",
    "bus.add_signal_watch()\n",
    "bus.connect(\"message\", bus_call, loop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Lets add probe to get informed of the meta data generated, we add probe to\n",
    "# the sink pad of the osd element, since by that time, the buffer would have\n",
    "# had got all the metadata.\n",
    "# osdsinkpad = nvosd.get_static_pad(\"sink\")\n",
    "# if not osdsinkpad:\n",
    "#     print(\" Unable to get sink pad of nvosd \\n\")\n",
    "\n",
    "# osdsinkpad.add_probe(Gst.PadProbeType.BUFFER, osd_sink_pad_buffer_probe, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting pipeline \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# start play back and listen to events\n",
    "print(\"Starting pipeline \\n\")\n",
    "pipeline.set_state(Gst.State.PLAYING)\n",
    "try:\n",
    "    loop.run()\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "# cleanup\n",
    "pipeline.set_state(Gst.State.NULL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from os.path import exists\n",
    "\n",
    "# file_exists = exists(path_to_file)"
   ]
  }
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