Dataflow and user query 1: Amber alert

1. USING Optasia;
2.  
3. //Extract video frames
4. rawframes =
5.     EXTRACT vid : int, //camera/video id
6.             fid : int, //frame id
7.             cid : int, //chunk id
8.             frame : string //video frame
9.     FROM SPARSE STREAMSET @"/my/v_wsdot/"
10.                 PATTERN @"t_%n.avi"
11.                 RANGE __serialnum = ["1","100"]
12.     USING VideoExtractor("300", "50");
13.  
14. //Detect license plates
15. lpr =
16.     PROCESS rawframes
17.     USING LPRProcessor("LP.model", "OCR.model")
18.     PRODUCE vid,
19.             fid,
20.             LP,
21.             Confidence;
22.  
23. //Extract RGB histogram feature
24. features_RGBHIST =
25.     PROCESS rawframes
26.     USING FeatureProcessor("RGBHIST:size=10")
27.     PRODUCE vid,
28.             fid,
29.             Feature;
30.  
31. //Extract HOG feature
32. features_HOG =
33.     PROCESS rawframes
34.     USING FeatureProcessor("HOG:dimh=64,dimw=64")
35.     PRODUCE vid,
36.             fid,
37.             Feature;
38.  
39. //Combine features
40. features_CarClassification =
41.     REDUCE
42.     (
43.         SELECT *
44.         FROM features_HOG
45.         UNION
46.         SELECT *
47.         FROM features_RGBHIST
48.     )
49.     ON vid, fid
50.     USING FeatureReducer;
51.  
52. //Apply classifier and predict vehicle type labels
53. labels_CarClassification =
54.     PROCESS features_CarClassification
55.     USING ClassifierProcessor(@"vehicle.model")
56.     PRODUCE vid,
57.             fid,
58.             label,
59.             confidence;
60.  
61. //Apply classifier and predict vehicle color labels
62. labels_ColorClassification =
63.     PROCESS features_RGBHIST
64.     USING ClassifierProcessor(@"color.model")
65.     PRODUCE vid,
66.             fid,
67.             label,
68.             confidence;
69.  
70. results =
71.     SELECT labels_CarClassification.vid,
72.            labels_CarClassification.fid
73.     FROM labels_CarClassification
74.          INNER JOIN
75.              lpr
76.          ON lpr.fid == labels_CarClassification.fid
77.             AND lpr.vid == labels_CarClassification.vid
78.          INNER JOIN
79.              labels_ColorClassification
80.          ON labels_ColorClassification.vid == labels_CarClassification.vid
81.             AND labels_ColorClassification.fid == labels_CarClassification.fid
82.     WHERE lpr.LP.StartsWith("A") AND labels_CarClassification.label == "suv"
83.           AND labels_ColorClassification.label == "red";

Dataflow and user query 2: Traffic violation

1. USING Optasia;
2.  
3. rawframes =
4.     EXTRACT vid : int, //camera/video id
5.             fid : int, //frame id
6.             cid : int, //chunk id
7.             frame : string //video frame
8.     FROM SPARSE STREAMSET @"/my/v_wsdot/"
9.                 PATTERN @"t_%n.avi"
10.                 RANGE __serialnum = ["1","100"]
11.     USING VideoExtractor("300", "50");
12.  
13. //Estimate traffic flow
14. counter =
15.     REDUCE rawframes
16.     ON vid, cid
17.     PRODUCE vid,
18.             fid,
19.             patch, //image patch for detected vehicles
20.             inbox, //vehicles passing which entry box
21.             fid_in, //time to pass the entry box
22.             outbox, //vehicles passing which exit box
23.             fid_out //time to pass the exit box
24.     USING TrackingReducer("L_lane_in,M_lane_in,R_lane_in", "L_lane_out,M_lane_out,R_lane_out", "MercerSt.tif");
25.  
26. //Extract HOG feature
27. features_HOG =
28.     PROCESS counter
29.     USING FeatureProcessor("HOG:dimh=64,dimw=64")
30.     PRODUCE vid,
31.             fid,
32.             Feature;
33.  
34. //Extract RGB histogram feature
35. features_RGBHIST =
36.     PROCESS counter
37.     USING FeatureProcessor("RGBHIST:size=10")
38.     PRODUCE vid,
39.             fid,
40.             Feature;
41.  
42. //Combine features
43. features_CarClassification =
44.     REDUCE
45.     (
46.         SELECT *
47.         FROM features_HOG
48.         UNION
49.         SELECT *
50.         FROM features_RGBHIST
51.     )
52.     ON vid, fid
53.     USING FeatureReducer;
54.  
55. //Apply classifier and predict vehicle type labels
56. labels_CarClassification =
57.     PROCESS features_CarClassification
58.     USING ClassifierProcessor(@"vehicle.model")
59.     PRODUCE vid,
60.             fid,
61.             label,
62.             confidence;
63.  
64. results =
65.     SELECT counter.*,
66.            labels_CarClassification.*
67.     FROM counter
68.          INNER JOIN
69.              labels_CarClassification
70.          ON counter.fid == labels_CarClassification.fid
71.             AND counter.vid == labels_CarClassification.vid
72.     WHERE inbox == "L_lane_in" AND outbox == "R_lane_out"
73.           AND labels_CarClassification.label == "truck";

Dataflow and user query 3: Re-identification

1. USING Optasia;
2.  
3. //Read existed Re-ID matrix
4. reid_mat =
5.     EXTRACT CamId_a : int,
6.             CamId_b : int,
7.             data : string
8.     FROM @"/my/reid/ReID_1_2.gz"
9.     USING ReIDDictExtractor();
10.  
11. //Extrat video frames
12. v_a =
13.     EXTRACT vid : int,
14.             fid : int,
15.             cid : int,
16.             frame : string
17.     FROM SPARSE STREAMSET @"/my/garageA/"
18.                 PATTERN @"G_%n.mp4"
19.                 RANGE __serialnum = ["1","100"]
20.     USING VideoExtractor("300", "50");
21.  
22. v_b =
23.     EXTRACT vid : int,
24.             fid : int,
25.             cid : int,
26.             frame : string
27.     FROM SPARSE STREAMSET @"/my/garageB/"
28.                 PATTERN @"G_%n.mp4"
29.                 RANGE __serialnum = ["1","100"]
30.     USING VideoExtractor("300", "50");
31.  
32. //Extract features on feed A
33. features_HOG_a =
34.     PROCESS v_a
35.     USING FeatureProcessor("HOG:dimh=64,dimw=64")
36.     PRODUCE vid,
37.             fid,
38.             Feature;
39.  
40. features_RGBHIST_a =
41.     PROCESS v_a
42.     USING FeatureProcessor("RGBHIST:size=10")
43.     PRODUCE vid,
44.             fid,
45.             Feature;
46.  
47. features_CarClassification_a =
48.     REDUCE
49.     (
50.         SELECT *
51.         FROM features_HOG_a
52.         UNION
53.         SELECT *
54.         FROM features_RGBHIST_a
55.     )
56.     ON vid, fid
57.     USING FeatureReducer;
58.  
59. //Apply classifier and predict vehicle type labels
60. type_a =
61.     PROCESS features_CarClassification_a
62.     USING ClassifierProcessor(@"vehicle.model")
63.     PRODUCE vid,
64.             fid,
65.             label,
66.             confidence;
67.  
68. //Extract features on feed B
69. features_HOG_b =
70.     PROCESS v_b
71.     USING FeatureProcessor("HOG:dimh=64,dimw=64")
72.     PRODUCE vid,
73.             fid,
74.             Feature;
75.  
76. features_RGBHIST_b =
77.     PROCESS v_b
78.     USING FeatureProcessor("RGBHIST:size=10")
79.     PRODUCE vid,
80.             fid,
81.             Feature;
82.  
83. features_CarClassification_b =
84.     REDUCE
85.     (
86.         SELECT *
87.         FROM features_HOG_b
88.         UNION
89.         SELECT *
90.         FROM features_RGBHIST_b
91.     )
92.     ON vid, fid
93.     USING FeatureReducer;
94.  
95. //Apply classifier and predict vehicle type labels
96. type_b =
97.     PROCESS features_CarClassification_b
98.     USING ClassifierProcessor(@"vehicle.model")
99.     PRODUCE vid,
100.             fid,
101.             label,
102.             confidence;
103.  
104. //Extract Re-ID features feed A
105. features_pyramidSILTP_a =
106.     PROCESS v_a
107.     USING FeatureProcessor("PYRAMIDMAXSILTPHIST")
108.     PRODUCE vid,
109.             fid,
110.             Feature;
111.  
112. features_pyramidHIST_a =
113.     PROCESS features_pyramidSILTP_a
114.     USING FeatureProcessor("PYRAMIDMAXJOINTHIST")
115.     PRODUCE v_a,
116.             fid,
117.             Feature;
118.  
119. features_reid_a =
120.     REDUCE
121.     (
122.         SELECT *
123.         FROM features_pyramidSILTP_a
124.         UNION
125.         SELECT *
126.         FROM features_pyramidHIST_a
127.     )
128.     ON vid, fid
129.     USING FeatureReducer;
130.  
131. //Extract Re-ID features feed B
132. features_pyramidSILTP_b =
133.     PROCESS v_b
134.     USING FeatureProcessor("PYRAMIDMAXSILTPHIST")
135.     PRODUCE vid,
136.             fid,
137.             Feature;
138.  
139. features_pyramidHIST_b =
140.     PROCESS v_b
141.     USING FeatureProcessor("PYRAMIDMAXJOINTHIST")
142.     PRODUCE vid,
143.             fid,
144.             Feature;
145.  
146. features_reid_b =
147.     REDUCE
148.     (
149.         SELECT *
150.         FROM features_pyramidSILTP_b
151.         UNION
152.         SELECT *
153.         FROM features_pyramidHIST_b
154.     )
155.     ON vid, fid
156.     USING FeatureReducer;
157.  
158. //Re-ID combiner
159. reid =
160.     COMBINE
161.     (
162.         SELECT features_reid_a.vid AS vid_a,
163.                features_reid_a.fid AS fid_a,
164.                features_reid_b.vid AS vid_b,
165.                features_reid_b.fid AS fid_b,
166.                features_reid_a.Feature AS Feature_a,
167.                features_reid_b.Feature AS Feature_b
168.         FROM features_pyramidHIST_a
169.              CROSS JOIN
170.                  features_pyramidHIST_b
171.     ) WITH reid_mat
172.     USING ReIDCombiner()
173.     PRODUCE vid_a,
174.             fid_a,
175.             vid_b,
176.             fid_b,
177.             score;
178.  
179. results =
180.     SELECT reid.*
181.     FROM reid
182.          INNER JOIN
183.              type_a
184.          ON reid.vid_a == type_a.vid AND reid.fid_a == type_a.fid
185.          INNER JOIN
186.              type_b
187.          ON reid.vid_b == type_b.vid AND reid.fid_b == type_b.fid
188.     WHERE reid.score > - 15
189.           AND type_a.label == "suv" AND type_b.label == "suv";