Google Cloud Video Intelligence provides the following code for parsing annotation results with object tracking:
features = [videointelligence.Feature.OBJECT_TRACKING]
context = videointelligence.VideoContext(segments=None)
request = videointelligence.AnnotateVideoRequest(input_uri=gs_video_path, features=features, video_context=context, output_uri=output_uri)
operation = video_client.annotate_video(request)
result = operation.result(timeout=3600)
object_annotations = result.annotation_results[0].object_annotations
for object_annotation in object_annotations:
print('Entity description: {}'.format(object_annotation.entity.description))
print('Segment: {}s to {}s'.format(
object_annotation.segment.start_time_offset.total_seconds(),
object_annotation.segment.end_time_offset.total_seconds()))
print('Confidence: {}'.format(object_annotation.confidence))
# Here we print only the bounding box of the first frame_annotation in the segment
frame_annotation = object_annotation.frames[0]
box = frame_annotation.normalized_bounding_box
timestamp = frame_annotation.time_offset.total_seconds()
timestamp_end = object_annotation.segment.end_time_offset.total_seconds()
print('Time offset of the first frame_annotation: {}s'.format(timestamp))
print('Bounding box position:')
print('\tleft : {}'.format(box.left))
print('\ttop : {}'.format(box.top))
print('\tright : {}'.format(box.right))
print('\tbottom: {}'.format(box.bottom))
print('\n')
However, I want to parse the json file that is generated via output_uri. The format of the json file is as following :
{
"annotation_results": [ {
"input_uri": "/production.supereye.co.uk/video/54V5x8q0CRU/videofile.mp4",
"segment": {
"start_time_offset": {
},
"end_time_offset": {
"seconds": 22,
"nanos": 966666000
}
},
"object_annotations": [ {
"entity": {
"entity_id": "/m/01yrx",
"description": "cat",
"language_code": "en-US"
},
"confidence": 0.91939145,
"frames": [ {
"normalized_bounding_box": {
"left": 0.17845993,
"top": 0.44048917,
"right": 0.5315634,
"bottom": 0.7752136
},
"time_offset": {
}
}, {
How can I use the example code to parse the JSON that is provided with output_uri ? What kind of conversion is needed for this ?
Using the file from output_uri
, you can parse the json using this code. I saved the file as response.json locally and will use this for parsing.
This is similar with your code above where it parses data at the 1st frame_annotation
. But this code lacks conversion of time offsets since the function used to convert is from a time object.
I commented start_end_offset
and end_time_offset
since it has 2 keys, seconds
and nano
. It's up to you which one would you like to use, just uncomment the lines and adjust accordingly.
import json
f = open('response.json', "r")
data = json.loads(f.read())
for results in data["annotation_results"]:
for obj_ann in results["object_annotations"]:
#start_time_offset = obj_ann["segment"]["start_time_offset"]["seconds"]
#end_time_offset = obj_ann["segment"]["end_time_offset"]["seconds"]
frame_annotation = obj_ann["frames"][0]
entity = obj_ann["entity"]["description"]
confidence = obj_ann["confidence"]
box = frame_annotation["normalized_bounding_box"]
time_offset = frame_annotation["time_offset"] #apparently this also has 2 keys. Look out for the other key which is `seconds`
print('Entity description: {}'.format(entity))
#print('Segment: {}s to {}s'.format(start_time_offset,end_time_offset))
print('Confidence: {}'.format(confidence))
#You can modify the code here if you encounter the `second` key
if 'nanos' not in time_offset:
print('No time offset in frame')
print('Bounding box position:')
print('\tleft : {}'.format(str(box["left"])))
print('\tleft : {}'.format(str(box["top"])))
print('\tleft : {}'.format(str(box["right"])))
print('\tleft : {}'.format(str(box["bottom"])))
else:
print('Time offset of the first frame_annotation: {}'.format(time_offset["nanos"]))
print('Bounding box position:')
print('\tleft : {}'.format(str(box["left"])))
print('\tleft : {}'.format(str(box["top"])))
print('\tleft : {}'.format(str(box["right"])))
print('\tleft : {}'.format(str(box["bottom"])))
For testing I used gs://cloud-samples-data/video/cat.mp4 and used its response: