mirror of
https://github.com/jehiah/TrafficSpeed.git
synced 2025-12-24 12:47:54 +08:00
clean up log output; apply mask to bitmask
This commit is contained in:
Jehiah Czebotar
@@ -10,7 +10,7 @@ read 10 random frames and generate a background from the averages
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function avg_background(f::VideoIO.VideoReader, rrc::Function)
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seekstart(f)
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bg = float32(convert(Image{ColorTypes.RGB{Float32}}, rrc(f)))
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println("rrc summary $(summary(bg))")
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# println("rrc summary $(summary(bg))")
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# bg = convert(Image{ColorTypes.RGB{Float32}}, frame)
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step = duration(f)/20
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@@ -19,7 +19,7 @@ function avg_background(f::VideoIO.VideoReader, rrc::Function)
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while count < 20
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total_pos += step
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count+=1
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println("generating background: seeking $step to $total_pos for frame $count")
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println("background frame $count @ $total_pos seconds")
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seek(f, total_pos)
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frame = float32(rrc(f))
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bg += frame
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@@ -2,6 +2,8 @@ using Images, Colors
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import Base: .^
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import FixedPointNumbers: UFixed8
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include("./mask.jl")
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# Absolute value is defined for RGB colors, but it's a little wonky -- it's the *sum* of the absolute values
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# of the components. It is exactly what we want, but it's not defined for arrays of RGBs, so we add that definition here:
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@vectorize_1arg AbstractRGB Base.abs
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@@ -18,10 +20,10 @@ function labelimg_base(img::Image, background::Image)
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# grayim(map(ColorTypes.RGB{Float32}, i))
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end
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function label(img::Image, background::Image, blur=[3,3], tolerance=0.06)
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function label(img::Image, background::Image, masks::Array, blur=[3,3], tolerance=0.06)
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i = imfilter_gaussian(grayim(abs((convert(Image{RGB{Float32}}, img) - convert(Image{RGB{Float32}}, background)).^2)),blur) .> tolerance
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i::BitMatrix
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label_components(i) # This is like MATLAB's bwlabel
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label_components(mask(i, masks)) # This is like MATLAB's bwlabel
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end
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# """
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@@ -35,8 +37,8 @@ end
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"""
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Show an image with labeled (by color) regions
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"""
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function labelimg_example(img::Image, background::Image, blur=[3,3], tolerance=0.06)
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labels = label(img, background, blur, tolerance)
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function labelimg_example(img::Image, background::Image, masks::Array, blur=[3,3], tolerance=0.06)
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labels = label(img, background, masks, blur, tolerance)
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# from https://github.com/JuliaGraphics/Colors.jl/blob/master/src/names_data.jl
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colors = [colorant"black", # this is the background
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colorant"red", colorant"yellow", colorant"green", colorant"blue",
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34
src/main.jl
34
src/main.jl
@@ -16,6 +16,7 @@ include("./base64img.jl")
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include("./mask.jl")
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include("./background.jl")
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include("./labelimg.jl")
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include("./positions.jl")
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jsonContentType = Dict{AbstractString,AbstractString}([("Content-Type", "application/json")])
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@@ -42,7 +43,7 @@ http = HttpHandler() do req::Request, res::Response
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f = VideoIO.openvideo(io)
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resp["frames"] = length(f)
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resp["duration_seconds"] = duration(f)
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println("$(resp["frames"])frames, duration: $(resp["duration_seconds"]) seconds")
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video_summary(f)
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img = read(f, Image)
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resp["video_resolution"] = "$(size(img.data, 1))x$(size(img.data, 2))"
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@@ -51,7 +52,6 @@ http = HttpHandler() do req::Request, res::Response
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println("Generating overview image (step 2)")
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resp["step_2_img"] = base64img("image/png", img)
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# println("img is $(resp["step_two_size"])")
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if haskey(job, "rotate") && job["rotate"] != 0.00001
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println("Rotating $(job["rotate"]) radians")
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@@ -62,11 +62,11 @@ http = HttpHandler() do req::Request, res::Response
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resp["step_3_img"] = base64img("image/png", img)
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if haskey(job, "bbox")
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println("cropping to $(job["bbox"])")
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println("cropping to [$(job["bbox"]["a"]["x"]):$(job["bbox"]["b"]["x"]), $(job["bbox"]["a"]["y"]):$(job["bbox"]["b"]["y"])]")
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# println("before crop $(summary(img))")
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job["bbox_region"] = (job["bbox"]["a"]["x"]:job["bbox"]["b"]["x"], job["bbox"]["a"]["y"]:job["bbox"]["b"]["y"])
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img = crop(img, job["bbox_region"])
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println("after crop $(summary(img))")
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println("Cropped image is $(summary(img))")
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else
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# set crop region to no-op size
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job["bbox_region"] = (1:size(img.data,1), 1:size(img.data, 2))
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@@ -75,8 +75,8 @@ http = HttpHandler() do req::Request, res::Response
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resp["step_4_img"] = base64img("image/png", img)
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if haskey(job, "masks")
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println("Applying masks: $(job["masks"])")
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masked = mask(img, job["masks"])
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# println("Applying masks: $(job["masks"])")
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masked = mask_img(img, job["masks"])
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resp["step_4_mask_img"] = base64img("image/png", masked)
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end
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@@ -105,28 +105,30 @@ http = HttpHandler() do req::Request, res::Response
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background = avg_background(f, rrc)
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resp["background_img"] = base64img("image/png", background)
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if haskey(job, "masks")
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background = mask(background, job["masks"])
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end
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# pick five frames
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frame_analysis = Array{Any, 1}()
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i = 0
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blur_arg=[job["blur"], job["blur"]]
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if haskey(job, "masks")
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mask_args = job["masks"]
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else
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mask_args = Array{Any,1}()
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end
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while i < 4
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e = Dict{AbstractString,Any}()
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pos = i * (duration(f)/5) # increment by a smaller fraction so we don't get the last frame
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pos = floor(Int, i * (duration(f)/5)) # increment by a smaller fraction so we don't get the last frame
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println("analyzing frame at $pos seconds")
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e["ts"] = pos
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seek(f, pos)
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frame = rrc(f)
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if haskey(job, "masks")
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frame = mask(frame, job["masks"])
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end
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e["highlight"] = base64img("image/png", labelimg_base(frame, background))
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e["colored"] = base64img("image/png", labelimg_example(frame, background, blur_arg, job["tolerance"]))
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# e["labels"] = label(frame, background)
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e["colored"] = base64img("image/png", labelimg_example(frame, background, mask_args, blur_arg, job["tolerance"]))
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e["positions"] = positions(label(frame, background, mask_args, blur_arg, job["tolerance"]))
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# println("$i positions json is $(JSON.json(e["positions"]))")
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push!(frame_analysis, e)
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i += 1
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end
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35
src/mask.jl
35
src/mask.jl
@@ -7,36 +7,35 @@ using Images
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# NullMask bool `json:"null_mask,omitempty"`
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# }
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function mask(A::Image, masks)
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println("$(summary(A))")
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# a = convert(Image{ColorTypes.RGB{Float64}}, A)
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# a = convert(Image{ColorTypes.RGB{UFixed8}}, A)
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# T = eltype(A.data)
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# a = convert(Image{ColorTypes.RGB{T}}, A)
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# 1920x1080 Images.Image{ColorTypes.RGB{FixedPointNumbers.UFixed{UInt8,8}},2,Array{ColorTypes.RGB{FixedPointNumbers.UFixed{UInt8,8}},2}}
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function mask_img(A::Image, masks::Array)
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fill = zero(eltype(A.data))
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# fill = zero(ColorTypes.RGB{UFixed8})
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for m in masks
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println("applying mask $m")
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if haskey(m, "null_mask")
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continue
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end
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if haskey(m, "start")
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println("masking [:, $(m["start"]):$(m["end"])]")
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A.data[:, m["start"]:m["end"]] = fill
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else
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bbox = m["bbox"]
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println("masking [$(bbox["a"]["x"]):$(bbox["b"]["x"]), $(bbox["a"]["y"]):$(bbox["b"]["y"])]")
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A.data[bbox["a"]["x"]:bbox["b"]["x"], bbox["a"]["y"]:bbox["b"]["y"]] = fill
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end
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end
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A
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end
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# function mask{T}(A::BitMatrix, maskData)
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# mask = imfilter_gaussian(grayim(abs((convert(Image{RGB{Float32}}, img) - convert(Image{RGB{Float32}}, background)).^2)),[3,3]) .> .06
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# mask[:,13:14] = false
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# mask[:,29:33] = false
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# mask[:,40:43] = false
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# mask[:,53:66] = false
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#
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# grayim(map(UFixed8, mask))
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function mask(A::BitMatrix, masks::Array)
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for m in masks
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if haskey(m, "null_mask")
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continue
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end
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if haskey(m, "start")
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A[:, m["start"]:m["end"]] = false
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else
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bbox = m["bbox"]
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A[bbox["a"]["x"]:bbox["b"]["x"], bbox["a"]["y"]:bbox["b"]["y"]] = false
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end
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end
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A
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end
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@@ -59,7 +59,7 @@ const tpl = `
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{{ if .Rotate }}
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<h2>Step 2: Rotation</h2>
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<p>Rotation Angle <code>{{.Rotate}} radians</code></p>
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<input type="hidden" name="rotate" value="{{.Rotate}}" />
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<input type="hidden" name="rotate" value="{{.Rotate | printf "%0.5f"}}" />
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<div><img src="{{.Response.Step3Img}}" style="width: 25%; height: 25%;"></div>
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{{ end }}
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@@ -113,6 +113,9 @@ const tpl = `
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<h2>Step 4: Mask Regions</h2>
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<p>Masked regions: {{range .Masks }}<code>{{.}}</code> {{end}}</p>
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<div><img src="{{.Response.Step4MaskImg}}" style="width: 40%; height: 40%;"></div>
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{{ range .Masks }}
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<input type="hidden" name="mask" value="{{.}}" />
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{{ end }}
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{{ end }}
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{{ if eq .Step "step_four" }}
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@@ -122,8 +125,8 @@ const tpl = `
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Depending on the visual perspective the masked rows should be closer to wheel position to account for
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tall vehicles in the lane.
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</p>
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<p>Instructions: Note the X and Y from the image, and enter masks as a row range <code>row:row</code>
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or a bounding box pair of coordinates <code>10x20 20x30</code>. To continue without masks enter a mask of <code>-</code>.</p>
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<p>Instructions: Note the X and Y from the image, and enter masks as a row range <kbd>row:row</kbd>
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or a bounding box pair of coordinates <kbd>10x20 20x30</kbd>. To continue without masks enter a mask of <kbd>-</kbd>.</p>
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<div class="form-group">
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<label>Mask: <input name="mask" type="text" /></label>
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@@ -150,27 +153,54 @@ const tpl = `
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{{ if eq .Step "step_five" }}
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<h2>Step 5: Object Detection</h2>
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<p>The threshold must be set for what size triggers vehicle detection.</p>
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<p>Background Image:</p>
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<img src="{{.Response.BackgroundImg}}" style="width: 50%; height: 50%;">
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<div class="form-group">
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<label>Blur (pixels): <input name="blur" id="blur" type="text" value="{{.Blur}}" /></label>
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</div>
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<p>The tunables below adjust what is detected as "active" in an image, and what is treated as a vehicle.</p>
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<div class="form-group">
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<label>Tolerance: <input name="tolerance" id="tolerance" type="text" value="{{.Tolerance}}" /></label>
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<span class="help-block">The required difference from the background.</span>
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</div>
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<div class="form-group">
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<label>Blur (pixels): <input name="blur" id="blur" type="text" value="{{.Blur}}" /></label>
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<span class="help-block">Bluring helps define features better and make a single blob for better detection.</span>
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</div>
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<div class="form-group">
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<label>Min Mass: <input name="min_mass" id="min_mass" type="text" value="{{.MinMass}}" /></label>
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<span class="help-block">Filters out small areas that are detected in the image (such as pedestrians).</span>
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</div>
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<button type="submit" class="btn">Check</button>
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<button type="submit" class="btn btn-primary">Continue</button>
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<p>Background Image:</p>
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<img src="{{.Response.BackgroundImg}}" style="width: 50%; height: 50%;">
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<div class="row">
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{{ range .Response.FrameAnalysis }}
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<div class="col-xs-12 col-md-8 col-lg-6">
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<p>Time index <code>{{.Timestamp}} seconds</code></p>
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<p>Active Image:</p>
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<h4>Time index <code>{{.Timestamp}} seconds</code></h4>
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<p>Active Image: (before masking)</p>
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<img src="{{.Highlight}}" class="img-responsive">
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<p>Detected Areas:</p>
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<p>Detected Areas: (after masking)</p>
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<img src="{{.Colored}}" class="img-responsive">
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{{ if .Positions }}
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<table class="table table-striped">
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<thead>
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<tr>
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<th></th><th>Mass</th><th>Position</th><th>Size</th>
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</tr>
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</thead>
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<tbody>
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{{ range $i, $p := .Positions }}
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<tr>
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<th>{{$i}}</th>
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<td>{{$p.Mass }} pixels</td>
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<td>{{$p.X | printf "%0.f"}}x{{$p.Y | printf "%0.f"}}</td>
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<td>{{$p.Size}}</td>
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</tr>
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{{ end }}
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</tbody>
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</table>
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{{ end }}
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</div>
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{{ end }}
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</div>
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@@ -241,6 +271,7 @@ type Project struct {
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Masks []Mask `json:"masks,omitempty"`
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Tolerance float64 `json:"tolerance"`
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Blur int64 `json:"blur"`
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MinMass int64 `json:"min_mass"`
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Step string `json:"step"`
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Response Response `json:"response,omitempty"`
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@@ -264,7 +295,36 @@ type FrameAnalysis struct {
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Timestamp float64 `json:"ts"`
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Highlight template.URL `json:"highlight,omitempty"`
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Colored template.URL `json:"colored,omitempty"`
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Labels interface{} `json:"labels,omitempty"`
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Positions []Position `json:"positions,omitempty"`
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}
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// Position matches Position in position.jl
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type Position struct {
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X float64 `json:"x"`
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Y float64 `json:"y"`
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Mass int `json:"mass"`
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XSpan []int `json:"xspan"` // [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]
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YSpan []int `json:"yspan"`
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}
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func (p Position) Span() string {
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mm := func(d []int) (min int, max int) {
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for i, n := range d {
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if n < min || i == 0 {
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min = n
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}
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if n > max || i == 0 {
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max = n
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}
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}
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return
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}
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xmin, xmax := mm(p.XSpan)
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ymin, ymax := mm(p.YSpan)
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return fmt.Sprintf("x:%d-%d y:%d-%d", xmin, xmax, ymin, ymax)
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}
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func (p Position) Size() string {
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return fmt.Sprintf("%dx%d", len(p.XSpan), len(p.YSpan))
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}
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func (p *Project) getStep() string {
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@@ -360,15 +420,18 @@ func (p *Project) Run(backend string) error {
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func main() {
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backend := flag.String("backend", "http://127.0.0.1:8000", "base path to backend processing service")
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flag.Parse()
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t := template.Must(template.New("webpage").Parse(tpl))
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http.Handle("/data/", http.StripPrefix("/data/", http.FileServer(http.Dir("../data/"))))
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http.HandleFunc("/", func(w http.ResponseWriter, req *http.Request) {
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t := template.Must(template.New("webpage").Parse(tpl))
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req.ParseForm()
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p := &Project{
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Filename: req.Form.Get("filename"),
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Blur: 3,
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Tolerance: 0.06,
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MinMass: 100,
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}
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if f, err := strconv.ParseFloat(req.Form.Get("rotate"), 64); err == nil {
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@@ -384,6 +447,11 @@ func main() {
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p.Blur = int64(i)
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}
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}
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if v := req.Form.Get("min_mass"); v != "" {
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if i, err := strconv.Atoi(v); err == nil {
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p.MinMass = int64(i)
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}
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}
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p.BBox = ParseBBox(req.Form.Get("bbox"))
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p1, p2 := req.Form.Get("point1"), req.Form.Get("point2")
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12
src/seek.jl
12
src/seek.jl
@@ -20,8 +20,7 @@ function Base.seek(avin::VideoIO.AVInput, time, video_stream = 1)
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base_per_frame = (c.time_base.num * c.ticks_per_frame * s.time_base.den / c.time_base.den * s.time_base.num)
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avg_frame_rate = s.avg_frame_rate.num / s.avg_frame_rate.den
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pos = floor(Int, time * base_per_frame * avg_frame_rate)
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println("c.time_base $(c.time_base) s.time_base $(s.time_base)")
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println("seeking ahead $(time) sec by increasing position $pos (frame rate $avg_frame_rate/sec)")
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println("seeking to $(time) sec @ position $pos (frame rate $avg_frame_rate/sec)")
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# Seek
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# pos (aka Timestamp) is in AVStream.time_base units or, if no stream is specified, in AV_TIME_BASE units.
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@@ -32,6 +31,15 @@ function Base.seek(avin::VideoIO.AVInput, time, video_stream = 1)
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return avin
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end
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function video_summary(v::VideoIO.VideoReader, video_stream=1)
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stream_info = v.avin.video_info[video_stream]
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s = stream_info.stream
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c = stream_info.codec_ctx
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avg_frame_rate = s.avg_frame_rate.num / s.avg_frame_rate.den
|
||||
println("duration: $(duration(v)) sec, $(length(v)) frames. frame rate: $avg_frame_rate/sec")
|
||||
println("codec time_base $(c.time_base) stream time_base $(s.time_base)")
|
||||
end
|
||||
|
||||
function duration(avin::VideoIO.AVInput, video_stream = 1)
|
||||
stream_info = avin.video_info[video_stream]
|
||||
return stream_info.stream.duration / stream_info.stream.time_base.den
|
||||
|
||||
Reference in New Issue
Block a user