Merge pull request #111 from QuPengfei/master

update to 20.1 for ffmpeg and gst

ad-insertion/ad-segment/Dockerfile

@@ -1,5 +1,5 @@
 
-FROM openvisualcloud/xeon-ubuntu1804-media-ffmpeg:19.10.1
+FROM openvisualcloud/xeon-ubuntu1804-media-ffmpeg:20.1
 RUN apt-get update && apt-get install -y -q youtube-dl bc wget && rm -rf /var/lib/apt/lists/*;
 
 ####

ad-insertion/ad-transcode/Dockerfile

@@ -1,5 +1,5 @@
 
-FROM openvisualcloud/xeon-ubuntu1804-media-ffmpeg:19.10.1
+FROM openvisualcloud/xeon-ubuntu1804-media-ffmpeg:20.1
 
 RUN DEBIAN_FRONTEND=noninteractive apt-get update && apt-get install -y -q --no-install-recommends nginx python3-tornado python3-urllib3 python3-requests python3-psutil python3-pip && rm -rf /var/lib/apt/lists/* && \
     pip3 install 'kafka-python>=1.4.7' 'kazoo>=2.6.1'

ad-insertion/analytics/VCAC-A/ffmpeg/Dockerfile

@@ -1,6 +1,6 @@
 # ssai_analytics_ffmpeg_vcac-a
 
-ARG base_name=openvisualcloud/vcaca-ubuntu1804-analytics-ffmpeg:19.11
+ARG base_name=openvisualcloud/vcaca-ubuntu1804-analytics-ffmpeg:20.1
 FROM ${base_name}
 
 # Fetch python3 and Install python3

ad-insertion/analytics/VCAC-A/ffmpeg/pipelines/emotion_recognition/1/pipeline.json

@@ -2,7 +2,7 @@
     "name": "emotion_recognition",
     "version": 1,
     "type": "FFmpeg",
-    "template":"-flags unaligned -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device /dev/dri/renderD128 -i \"{source[uri]}\" -vf \"detect=model={models[face_detection_retail][1][network]}:model_proc=\"{models[face_detection_retail][1][proc]}\":interval=\"{parameters[every-nth-frame]}\":device=HDDL,classify=model=\"{models[emotion_recognition][1][network]}\":model_proc=\"{models[emotion_recognition][1][proc]}\":device=HDDL\"",
+    "template":"-flags unaligned -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device /dev/dri/renderD128 -i \"{source[uri]}\" -vf \"detect=model={models[face_detection_retail][1][network]}:model_proc=\"{models[face_detection_retail][1][proc]}\":interval=\"{parameters[every-nth-frame]}\":device=HDDL,classify=model=\"{models[emotion_recognition][1][network]}\":model_proc=\"{models[emotion_recognition][1][proc]}\":device=HDDL,metaconvert=converter=json:method=all:source=NULL:tags=NULL\"",
     "description":"Emotion Recognition",
     "parameters": {
         "type" : "object",

ad-insertion/analytics/VCAC-A/ffmpeg/pipelines/face_recognition/1/pipeline.json

@@ -2,7 +2,7 @@
     "name": "face_recognition",
     "version": 1,
     "type": "FFmpeg",
-    "template":"-flags unaligned -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device /dev/dri/renderD128 -i \"{source[uri]}\" -vf \"detect=model={models[face_detection_retail][1][network]}:model_proc=\"{models[face_detection_retail][1][proc]}\":interval=\"{parameters[every-nth-frame]}\":device=HDDL,classify=model=\"{models[face_reidentification][1][network]}\":model_proc=\"{models[face_reidentification][1][proc]}\":device=HDDL\",identify=gallery=\"/home/gallery/face_gallery_FP16/gallery.json\"",
+    "template":"-flags unaligned -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device /dev/dri/renderD128 -i \"{source[uri]}\" -vf \"detect=model={models[face_detection_retail][1][network]}:model_proc=\"{models[face_detection_retail][1][proc]}\":interval=\"{parameters[every-nth-frame]}\":device=HDDL,classify=model=\"{models[face_reidentification][1][network]}\":model_proc=\"{models[face_reidentification][1][proc]}\":device=HDDL\",identify=gallery=\"/home/gallery/face_gallery_FP16/gallery.json,metaconvert=converter=json:method=all:source=NULL:tags=NULL\"",
     "description":"Face Recognition",
     "parameters": {
         "type" : "object",

ad-insertion/analytics/VCAC-A/ffmpeg/pipelines/object_detection/1/pipeline.json

@@ -2,7 +2,7 @@
     "name": "object_detection",
     "version": 1,
     "type": "FFmpeg",
-    "template":"-flags unaligned -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device /dev/dri/renderD128 -i \"{source[uri]}\" -vf \"detect=model={models[object_detection][1][network]}:device=HDDL:model_proc=\"{models[object_detection][1][proc]}\":interval={parameters[every-nth-frame]}\"",
+    "template":"-flags unaligned -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device /dev/dri/renderD128 -i \"{source[uri]}\" -vf \"detect=model={models[object_detection][1][network]}:device=HDDL:model_proc=\"{models[object_detection][1][proc]}\":interval={parameters[every-nth-frame]},metaconvert=converter=json:method=all:source=NULL:tags=NULL\"",
     "description": "Object Detection",
     "parameters": {
         "type" : "object",

ad-insertion/analytics/VCAC-A/gst/Dockerfile

@@ -1,13 +1,11 @@
 # ssai_analytics_gst_vcac-a 
 
-FROM openvisualcloud/vcaca-ubuntu1804-analytics-gst:19.11
+FROM openvisualcloud/vcaca-ubuntu1804-analytics-gst:20.1
 
 # Fetch python3 and Install python3
 RUN DEBIAN_FRONTEND=noninteractive apt-get update && apt-get install -y -q --no-install-recommends libjson-c3 python3-gst-1.0 python3-jsonschema python3-gi python3-requests python3-tornado python3-pip python3-setuptools python3-wheel &&  rm -rf /var/lib/apt/lists/* && \
     pip3 install 'kafka-python>=1.4.7' 'kazoo>=2.6.1'
 
-#COPY ./app/server/requirements.txt /
-
 COPY app /home/
 COPY models/ /home/models/
 COPY gallery/ /home/gallery/

ad-insertion/analytics/Xeon/ffmpeg/Dockerfile

@@ -1,6 +1,6 @@
 # ssai_analytics_ffmpeg_xeon
 
-From openvisualcloud/xeon-ubuntu1804-analytics-ffmpeg:19.11
+From openvisualcloud/xeon-ubuntu1804-analytics-ffmpeg:20.1
 
 # Fetch python3 and Install python3
 RUN DEBIAN_FRONTEND=noninteractive apt-get update && apt-get install -y -q --no-install-recommends python3-gst-1.0 python3-jsonschema python3-pip && rm -rf /var/lib/apt/lists/* && \

ad-insertion/analytics/Xeon/ffmpeg/pipelines/emotion_recognition/1/pipeline.json

@@ -2,7 +2,7 @@
     "name": "emotion_recognition",
     "version": 1,
     "type": "FFmpeg",
-    "template":"-i \"{source[uri]}\" -vf \"detect=model={models[face_detection_retail][1][network]}:model_proc=\"{models[face_detection_retail][1][proc]}\":interval=\"{parameters[every-nth-frame]}\":device=CPU,classify=model=\"{models[emotion_recognition][1][network]}\":model_proc=\"{models[emotion_recognition][1][proc]}\":device=CPU\"",
+    "template":"-i \"{source[uri]}\" -vf \"detect=model={models[face_detection_retail][1][network]}:model_proc=\"{models[face_detection_retail][1][proc]}\":interval=\"{parameters[every-nth-frame]}\":device=CPU,classify=model=\"{models[emotion_recognition][1][network]}\":model_proc=\"{models[emotion_recognition][1][proc]}\":device=CPU,metaconvert=converter=json:method=all:source=NULL:tags=NULL\"",
     "description":"Emotion Recognition",
     "parameters": {
         "type" : "object",

ad-insertion/analytics/Xeon/ffmpeg/pipelines/face_recognition/1/pipeline.json

@@ -2,7 +2,7 @@
     "name": "face_recognition",
     "version": 1,
     "type": "FFmpeg",
-    "template":"-i \"{source[uri]}\" -vf \"detect=model={models[face_detection_retail][1][network]}:model_proc=\"{models[face_detection_retail][1][proc]}\":interval=\"{parameters[every-nth-frame]}\":device=CPU,classify=model=\"{models[face_reidentification][1][network]}\":model_proc=\"{models[face_reidentification][1][proc]}\":device=CPU,identify=gallery=\"/home/gallery/face_gallery_FP32/gallery.json\"\"",
+    "template":"-i \"{source[uri]}\" -vf \"detect=model={models[face_detection_retail][1][network]}:model_proc=\"{models[face_detection_retail][1][proc]}\":interval=\"{parameters[every-nth-frame]}\":device=CPU,classify=model=\"{models[face_reidentification][1][network]}\":model_proc=\"{models[face_reidentification][1][proc]}\":device=CPU,identify=gallery=\"/home/gallery/face_gallery_FP32/gallery.json\",metaconvert=converter=json:method=all:source=NULL:tags=NULL\"",
     "description":"Face Recognition Pipeline",
     "parameters": {
         "type" : "object",

ad-insertion/analytics/Xeon/ffmpeg/pipelines/object_detection/1/pipeline.json

@@ -2,7 +2,7 @@
     "name": "object_detection",
     "version": 1,
     "type": "FFmpeg",
-    "template":"-i \"{source[uri]}\" -vf \"detect=model={models[object_detection][1][network]}:model_proc=\"{models[object_detection][1][proc]}\":interval={parameters[every-nth-frame]}:device=CPU\"", 
+    "template":"-i \"{source[uri]}\" -vf \"detect=model={models[object_detection][1][network]}:model_proc=\"{models[object_detection][1][proc]}\":interval={parameters[every-nth-frame]}:device=CPU,metaconvert=converter=json:method=all:source=NULL:tags=NULL\"", 
     "description": "Object Detection",
     "parameters": {
         "type" : "object",

ad-insertion/analytics/Xeon/gst/Dockerfile

@@ -1,6 +1,6 @@
 # ssai_analytics_gst_xeon
 
-FROM openvisualcloud/xeon-ubuntu1804-analytics-gst:19.11
+FROM openvisualcloud/xeon-ubuntu1804-analytics-gst:20.1
 
 # Fetch python3 and Install python3
 RUN DEBIAN_FRONTEND=noninteractive apt-get update && apt-get install -y -q python3-gst-1.0 python3-jsonschema python3-pip ca-certificates && rm -rf /var/lib/apt/lists/* && \

ad-insertion/analytics/app/modules/FFmpegPipeline.py

@@ -153,6 +153,23 @@ def _add_default_models(self,args):
                         device = FFmpegPipeline.DEVICEID_MAP[int(filter_params['device'])]
                 filter_params["model"] = ModelManager.get_default_network_for_device(device,filter_params["model"])
                 new_filters.append(self._join_filter_params(filter_params))
+            elif (filter_params['type'] == "metaconvert"):
+                # use the file to send the tags info to ffmpeg 
+                tmp_file = "/tmp/timestamp"
+                if "tags" in self.request:
+                    try:
+                        tmp_tags=""
+                        for key in self.request["tags"]:
+                            #filter_params["tags"] = "{\"%s\":%s}" % (key, self.request["tags"][key])
+                            tmp_tags = "{\"%s\":%s}" % (key, self.request["tags"][key])
+                        with open(tmp_file,'w') as f:
+                            f.write(tmp_tags)
+                    except Exception:
+                        logger.error("Error adding tags")
+                source_uri ="source=" + "'" + self.request["source"]["uri"].replace(":","\\:") + "'"
+                filter_params_str = self._join_filter_params(filter_params).replace("source=NULL",source_uri)
+                filter_params_str = filter_params_str.replace("tags=NULL","tags=file|"+tmp_file)
+                new_filters.append(filter_params_str)
             else:
                 new_filters.append(_filter)
         args[vf_index+1] =','.join(new_filters)
@@ -164,9 +181,7 @@ def start(self):
         self._ffmpeg_launch_string = string.Formatter().vformat(self.template, [], self.request)
         args = ['ffmpeg']
         args.extend(shlex.split(self._ffmpeg_launch_string))
-        iemetadata_args = ["-f", "iemetadata", "-source_url", self.request["source"]["uri"]]
-
-        self._add_tags(iemetadata_args)
+        iemetadata_args = ["-f", "metapublish", "-method", "1", "-output_format", "stream"]
 
         if 'destination' in self.request:
             if self.request['destination']['type'] == "kafka":

ad-insertion/analytics/app/modules/GstGVAJSONMeta.py

@@ -6,7 +6,7 @@
 
 from ctypes import *  # pylint: disable=unused-wildcard-import
 
-clib = CDLL("/usr/lib/x86_64-linux-gnu/gstreamer-1.0/libgstvideoanalyticsmeta.so")
+clib = CDLL("/usr/local/lib/x86_64-linux-gnu/gstreamer-1.0/libgstvideoanalyticsmeta.so")
 
 # json meta
 

common/abr_hls_dash.py

@@ -40,7 +40,7 @@ def check_renditions(frame_height, renditions=renditions_sample):
     return min_res
 
 def GetABRCommand(in_file, target, streaming_type, renditions=renditions_sample, duration=2,segment_num=0,fade_type=None,content_type=None):
-    ffprobe_cmd = ["/usr/bin/ffprobe", "-v", "quiet", "-print_format", "json", "-show_streams",in_file]
+    ffprobe_cmd = ["ffprobe", "-v", "quiet", "-print_format", "json", "-show_streams",in_file]
 
     process_id = subprocess.Popen(ffprobe_cmd,stdout=subprocess.PIPE)
     # the `multiprocessing.Process` process will wait until
@@ -77,7 +77,7 @@ def GetABRCommand(in_file, target, streaming_type, renditions=renditions_sample,
 
     cmd = []
     cmd_abr = []
-    cmd_base = ["/usr/bin/ffmpeg", "-hide_banner", "-y","-i", in_file]
+    cmd_base = ["ffmpeg", "-hide_banner", "-y","-i", in_file]
     if clip_a_duration == 0 and content_type == "ad":
         cmd_base += ["-f", "lavfi", "-i", "anullsrc=channel_layout=stereo:sample_rate="+str(44100)]
     cmd_misc = ["-hide_banner", "-y"]
@@ -168,7 +168,7 @@ def GetABRCommand(in_file, target, streaming_type, renditions=renditions_sample,
 
 def GetFadeCommand(in_file, target, fade_type):
     # ffprobe -v quiet -print_format json -show_streams
-    ffprobe_cmd = ["/usr/bin/ffprobe", "-v", "quiet", "-print_format", "json", "-show_streams",in_file]
+    ffprobe_cmd = ["ffprobe", "-v", "quiet", "-print_format", "json", "-show_streams",in_file]
 
     process_id = subprocess.Popen(ffprobe_cmd,stdout=subprocess.PIPE)
     # the `multiprocessing.Process` process will wait until
@@ -192,7 +192,7 @@ def GetFadeCommand(in_file, target, fade_type):
         a_st = (int)(clip_a_duration - duration)
 
     cmd = []
-    cmd_base = ["/usr/bin/ffmpeg", "-i", in_file]
+    cmd_base = ["ffmpeg", "-i", in_file]
     cmd_fade_in_out = ["-af", "afade="+fade_type+":"+"st="+str(a_st)+":"+"d="+str(duration), "-c:v", "copy"]
 
     cmd = cmd_base + cmd_fade_in_out

content-provider/archive/Dockerfile

@@ -1,5 +1,5 @@
 
-FROM openvisualcloud/xeon-ubuntu1804-media-ffmpeg:19.10.1
+FROM openvisualcloud/xeon-ubuntu1804-media-ffmpeg:20.1
 RUN apt-get update && apt-get install -y -q youtube-dl bc wget && rm -rf /var/lib/apt/lists/*;
 
 ####

content-provider/transcode/Dockerfile

@@ -1,5 +1,5 @@
 
-FROM openvisualcloud/xeon-ubuntu1804-media-ffmpeg:19.10.1
+FROM openvisualcloud/xeon-ubuntu1804-media-ffmpeg:20.1
 
 RUN DEBIAN_FRONTEND=noninteractive apt-get update && apt-get install -y -q --no-install-recommends nginx python3-tornado python3-urllib3 python3-requests python3-psutil python3-pip && rm -rf /var/lib/apt/lists/* && \
     pip3 install 'kafka-python>=1.4.7' 'kazoo>=2.6.1'