diff --git a/src/assets/target.svg b/src/assets/target.svg new file mode 100644 index 0000000..0c71e01 --- /dev/null +++ b/src/assets/target.svg @@ -0,0 +1,14 @@ + + + + + + + + + + + + + + diff --git a/src/models/abdomen-mini/descript.json b/src/models/abdomen-mini/descript.json new file mode 100644 index 0000000..bbe8163 --- /dev/null +++ b/src/models/abdomen-mini/descript.json @@ -0,0 +1,11 @@ +{ + "version": "0.0.0-n1", + "region": "Coco", + "size": 640, + "epochs": 1000, + "name": "coco128 test", + "yolo-version": "8.1.20 docker", + "date": "2024-03-12", + "export": "coco128.yaml" +} + diff --git a/src/models/abdomen-mini/group1-shard1of4.bin b/src/models/abdomen-mini/group1-shard1of4.bin new file mode 100644 index 0000000..f635530 Binary files /dev/null and b/src/models/abdomen-mini/group1-shard1of4.bin differ diff --git a/src/models/abdomen-mini/group1-shard2of4.bin b/src/models/abdomen-mini/group1-shard2of4.bin new file mode 100644 index 0000000..99c734b Binary files /dev/null and b/src/models/abdomen-mini/group1-shard2of4.bin differ diff --git a/src/models/abdomen-mini/group1-shard3of4.bin b/src/models/abdomen-mini/group1-shard3of4.bin new file mode 100644 index 0000000..5cd390d Binary files /dev/null and b/src/models/abdomen-mini/group1-shard3of4.bin differ diff --git a/src/models/abdomen-mini/group1-shard4of4.bin b/src/models/abdomen-mini/group1-shard4of4.bin new file mode 100644 index 0000000..54fa89d Binary files /dev/null and b/src/models/abdomen-mini/group1-shard4of4.bin differ diff --git a/src/models/abdomen-mini/metadata.yaml b/src/models/abdomen-mini/metadata.yaml new file mode 100644 index 0000000..7414da6 --- /dev/null +++ b/src/models/abdomen-mini/metadata.yaml @@ -0,0 +1,92 @@ +description: Ultralytics best model trained on /usr/src/ultralytics/ultralytics/cfg/datasets/coco128.yaml +author: Ultralytics +license: AGPL-3.0 https://ultralytics.com/license +date: '2024-03-12T16:25:00.089873' +version: 8.1.20 +stride: 32 +task: detect +batch: 1 +imgsz: +- 640 +- 640 +names: + 0: person + 1: bicycle + 2: car + 3: motorcycle + 4: airplane + 5: bus + 6: train + 7: truck + 8: boat + 9: traffic light + 10: fire hydrant + 11: stop sign + 12: parking meter + 13: bench + 14: bird + 15: cat + 16: dog + 17: horse + 18: sheep + 19: cow + 20: elephant + 21: bear + 22: zebra + 23: giraffe + 24: backpack + 25: umbrella + 26: handbag + 27: tie + 28: suitcase + 29: frisbee + 30: skis + 31: snowboard + 32: sports ball + 33: kite + 34: baseball bat + 35: baseball glove + 36: skateboard + 37: surfboard + 38: tennis racket + 39: bottle + 40: wine glass + 41: cup + 42: fork + 43: knife + 44: spoon + 45: bowl + 46: banana + 47: apple + 48: sandwich + 49: orange + 50: broccoli + 51: carrot + 52: hot dog + 53: pizza + 54: donut + 55: cake + 56: chair + 57: couch + 58: potted plant + 59: bed + 60: dining table + 61: toilet + 62: tv + 63: laptop + 64: mouse + 65: remote + 66: keyboard + 67: cell phone + 68: microwave + 69: oven + 70: toaster + 71: sink + 72: refrigerator + 73: book + 74: clock + 75: vase + 76: scissors + 77: teddy bear + 78: hair drier + 79: toothbrush diff --git a/src/models/abdomen-mini/model.json b/src/models/abdomen-mini/model.json new file mode 100644 index 0000000..a473f58 --- /dev/null +++ b/src/models/abdomen-mini/model.json @@ -0,0 +1 @@ +{"format": "graph-model", "generatedBy": "2.9.0", "convertedBy": "TensorFlow.js Converter v3.15.0", "signature": {"outputs": {"Identity:0": {"name": "Identity:0"}}}, "modelTopology": {"node": [{"name": "ConstantFolding/PartitionedCall/model_3/tf.math.divide/truediv_recip", "op": "Const", "attr": {"dtype": {"type": "DT_FLOAT"}, "value": {"tensor": {"dtype": "DT_FLOAT", "tensorShape": {"dim": [{"size": "1"}, {"size": "1"}, {"size": "1"}]}}}}}, {"name": "1336", "op": "Const", "attr": {"value": {"tensor": {"dtype": "DT_FLOAT", "tensorShape": {"dim": [{"size": "1"}, {"size": "2"}, {"size": "8400"}]}}}, "dtype": {"type": "DT_FLOAT"}}}, {"name": "1328", "op": "Const", "attr": 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"truck", + "boat", + "traffic light", + "stop sign", + "bench", + "bird", + "cat", + "dog", + "horse", + "elephant", + "bear", + "zebra", + "giraffe", + "backpack", + "umbrella", + "handbag", + "tie", + "suitcase", + "frisbee", + "skis", + "snowboard", + "sports ball", + "kite", + "baseball bat", + "baseball glove", + "skateboard", + "tennis racket", + "bottle", + "wine glass", + "cup", + "fork", + "knife", + "spoon", + "bowl", + "banana", + "sandwich", + "orange", + "broccoli", + "carrot", + "hot dog", + "pizza", + "donut", + "cake", + "chair", + "couch", + "potted plant", + "bed", + "dining table", + "toilet", + "tv", + "laptop", + "mouse", + "remote", + "cell phone", + "microwave", + "oven", + "sink", + "refrigerator", + "book", + "clock", + "vase", + "scissors", + "teddy bear", + "toothbrush" +] \ No newline at end of file diff --git a/src/models/abdomen/descript.json b/src/models/abdomen/descript.json new file mode 100644 index 0000000..bbe8163 --- /dev/null +++ b/src/models/abdomen/descript.json @@ -0,0 +1,11 @@ +{ + "version": "0.0.0-n1", + "region": "Coco", + "size": 640, + "epochs": 1000, + "name": "coco128 test", + "yolo-version": "8.1.20 docker", + "date": "2024-03-12", + "export": "coco128.yaml" +} + diff --git a/src/models/abdomen/group1-shard1of4.bin b/src/models/abdomen/group1-shard1of4.bin new file mode 100644 index 0000000..f635530 Binary files /dev/null and b/src/models/abdomen/group1-shard1of4.bin differ diff --git a/src/models/abdomen/group1-shard2of4.bin b/src/models/abdomen/group1-shard2of4.bin new file mode 100644 index 0000000..99c734b Binary files /dev/null and b/src/models/abdomen/group1-shard2of4.bin differ diff --git a/src/models/abdomen/group1-shard3of4.bin b/src/models/abdomen/group1-shard3of4.bin new file mode 100644 index 0000000..5cd390d Binary files /dev/null and b/src/models/abdomen/group1-shard3of4.bin differ diff --git a/src/models/abdomen/group1-shard4of4.bin b/src/models/abdomen/group1-shard4of4.bin new file mode 100644 index 0000000..54fa89d Binary files /dev/null and b/src/models/abdomen/group1-shard4of4.bin differ diff --git a/src/models/abdomen/metadata.yaml b/src/models/abdomen/metadata.yaml new file mode 100644 index 0000000..7414da6 --- /dev/null +++ b/src/models/abdomen/metadata.yaml @@ -0,0 +1,92 @@ +description: Ultralytics best model trained on /usr/src/ultralytics/ultralytics/cfg/datasets/coco128.yaml +author: Ultralytics +license: AGPL-3.0 https://ultralytics.com/license +date: '2024-03-12T16:25:00.089873' +version: 8.1.20 +stride: 32 +task: detect +batch: 1 +imgsz: +- 640 +- 640 +names: + 0: person + 1: bicycle + 2: car + 3: motorcycle + 4: airplane + 5: bus + 6: train + 7: truck + 8: boat + 9: traffic light + 10: fire hydrant + 11: stop sign + 12: parking meter + 13: bench + 14: bird + 15: cat + 16: dog + 17: horse + 18: sheep + 19: cow + 20: elephant + 21: bear + 22: zebra + 23: giraffe + 24: backpack + 25: umbrella + 26: handbag + 27: tie + 28: suitcase + 29: frisbee + 30: skis + 31: snowboard + 32: sports ball + 33: kite + 34: baseball bat + 35: baseball glove + 36: skateboard + 37: surfboard + 38: tennis racket + 39: bottle + 40: wine glass + 41: cup + 42: fork + 43: knife + 44: spoon + 45: bowl + 46: banana + 47: apple + 48: sandwich + 49: orange + 50: broccoli + 51: carrot + 52: hot dog + 53: pizza + 54: donut + 55: cake + 56: chair + 57: couch + 58: potted plant + 59: bed + 60: dining table + 61: toilet + 62: tv + 63: laptop + 64: mouse + 65: remote + 66: keyboard + 67: cell phone + 68: microwave + 69: oven + 70: toaster + 71: sink + 72: refrigerator + 73: book + 74: clock + 75: vase + 76: scissors + 77: teddy bear + 78: hair drier + 79: toothbrush diff --git a/src/models/abdomen/model.json b/src/models/abdomen/model.json new file mode 100644 index 0000000..a473f58 --- /dev/null +++ b/src/models/abdomen/model.json @@ -0,0 +1 @@ +{"format": "graph-model", "generatedBy": "2.9.0", "convertedBy": "TensorFlow.js Converter v3.15.0", "signature": 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"int32"}, {"name": "1148", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_9/ones_like", "shape": [4], "dtype": "int32"}, {"name": "1150", "shape": [3, 3, 64, 64], "dtype": "float32"}, {"name": "1152", "shape": [64], "dtype": "float32"}, {"name": "1154", "shape": [3, 3, 64, 64], "dtype": "float32"}, {"name": "1156", "shape": [64], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_6/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1162", "shape": [1, 1, 192, 128], "dtype": "float32"}, {"name": "1164", "shape": [128], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_9/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1196", "shape": [1, 1, 192, 128], "dtype": "float32"}, {"name": "1198", "shape": [128], "dtype": "float32"}, {"name": "1200", "shape": [4], "dtype": "int32"}, {"name": "1202", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_13/ones_like", "shape": [4], "dtype": "int32"}, {"name": "1204", "shape": [3, 3, 64, 64], "dtype": "float32"}, {"name": "1206", "shape": [64], "dtype": "float32"}, {"name": "1208", "shape": [3, 3, 64, 64], "dtype": "float32"}, {"name": "1210", "shape": [64], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_588/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1216", "shape": [1, 1, 192, 128], "dtype": "float32"}, {"name": "1218", "shape": [128], "dtype": "float32"}, {"name": "1220", "shape": [4, 2], "dtype": "int32"}, {"name": "1222", "shape": [3, 3, 128, 128], "dtype": "float32"}, {"name": "1224", "shape": [128], "dtype": "float32"}, {"name": "1126", "shape": [4], "dtype": "int32"}, {"name": "1128", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_6/ones_like", "shape": [4], "dtype": "int32"}, {"name": "1096", "shape": [4], "dtype": "int32"}, {"name": "1098", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_4/ones_like", "shape": 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"PartitionedCall/model_3/tf.strided_slice_1/ones_like", "shape": [4], "dtype": "int32"}, {"name": "1012", "shape": [3, 3, 16, 16], "dtype": "float32"}, {"name": "1014", "shape": [16], "dtype": "float32"}, {"name": "1016", "shape": [3, 3, 16, 16], "dtype": "float32"}, {"name": "1018", "shape": [16], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1024", "shape": [1, 1, 48, 32], "dtype": "float32"}, {"name": "1026", "shape": [32], "dtype": "float32"}, {"name": "1028", "shape": [4, 2], "dtype": "int32"}, {"name": "1030", "shape": [3, 3, 32, 64], "dtype": "float32"}, {"name": "1032", "shape": [64], "dtype": "float32"}, {"name": "1034", "shape": [1, 1, 64, 64], "dtype": "float32"}, {"name": "1036", "shape": [64], "dtype": "float32"}, {"name": "1038", "shape": [4], "dtype": "int32"}, {"name": "1040", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_3/ones_like", "shape": [4], "dtype": 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[4], "dtype": "int32"}, {"name": "1078", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_5/ones_like", "shape": [4], "dtype": "int32"}, {"name": "1080", "shape": [3, 3, 64, 64], "dtype": "float32"}, {"name": "1082", "shape": [64], "dtype": "float32"}, {"name": "1084", "shape": [3, 3, 64, 64], "dtype": "float32"}, {"name": "1086", "shape": [64], "dtype": "float32"}, {"name": "1088", "shape": [3, 3, 64, 64], "dtype": "float32"}, {"name": "1090", "shape": [64], "dtype": "float32"}, {"name": "1092", "shape": [3, 3, 64, 64], "dtype": "float32"}, {"name": "1094", "shape": [64], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_2/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1100", "shape": [1, 1, 256, 128], "dtype": "float32"}, {"name": "1102", "shape": [128], "dtype": "float32"}, {"name": "1104", "shape": [4, 2], "dtype": "int32"}, {"name": "1106", "shape": [3, 3, 128, 256], "dtype": "float32"}, {"name": "1108", "shape": [256], "dtype": "float32"}, {"name": "1110", "shape": [1, 1, 256, 256], "dtype": "float32"}, {"name": "1112", "shape": [256], "dtype": "float32"}, {"name": "1114", "shape": [4], "dtype": "int32"}, {"name": "1116", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_7/ones_like", "shape": [4], "dtype": "int32"}, {"name": "1118", "shape": [3, 3, 128, 128], "dtype": "float32"}, {"name": "1120", "shape": [128], "dtype": "float32"}, {"name": "1122", "shape": [3, 3, 128, 128], "dtype": "float32"}, {"name": "1124", "shape": [128], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_3/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1130", "shape": [1, 1, 384, 256], "dtype": "float32"}, {"name": "1132", "shape": [256], "dtype": "float32"}, {"name": "1134", "shape": [1, 1, 256, 128], "dtype": "float32"}, {"name": "1136", "shape": [128], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_4/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1138", "shape": [1, 1, 512, 256], "dtype": "float32"}, {"name": "1140", "shape": [256], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_589/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1226", "shape": [1, 1, 384, 256], "dtype": "float32"}, {"name": "1228", "shape": [256], "dtype": "float32"}, {"name": "1230", "shape": [4], "dtype": "int32"}, {"name": "1232", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_15/ones_like", "shape": [4], "dtype": "int32"}, {"name": "1234", "shape": [3, 3, 128, 128], "dtype": "float32"}, {"name": "1236", "shape": [128], "dtype": "float32"}, {"name": "1238", "shape": [3, 3, 128, 128], "dtype": "float32"}, {"name": "1240", "shape": [128], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_591/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1246", "shape": [1, 1, 384, 256], "dtype": "float32"}, {"name": "1248", "shape": [256], "dtype": "float32"}, {"name": "1256", "shape": [3, 3, 256, 80], "dtype": "float32"}, {"name": "1266", "shape": [80], "dtype": "float32"}, {"name": "1280", "shape": [3, 3, 80, 80], "dtype": "float32"}, {"name": "1290", "shape": [80], "dtype": "float32"}, {"name": "1302", "shape": [1, 1, 80, 80], "dtype": "float32"}, {"name": "1316", "shape": [80], "dtype": "float32"}, {"name": "PartitionedCall/model_3/tf.concat_592/concat/axis", "shape": [], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.compat.v1.transpose_1158/transpose/perm", "shape": [4], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.reshape_2/Reshape/shape", "shape": [3], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.concat_593/concat/axis", "shape": [], "dtype": "int32"}, {"name": "1342", "shape": [3], "dtype": "int32"}, {"name": "1344", "shape": [3], "dtype": "int32"}, {"name": "PartitionedCall/model_3/tf.strided_slice_17/StridedSlice/strides", "shape": [3], "dtype": "int32"}, {"name": "PartitionedCall/model_3/output0/concat/axis", "shape": [], "dtype": "int32"}]}]} \ No newline at end of file diff --git a/src/pages/camera-mixin.js b/src/pages/camera-mixin.js index 97e9a07..f04e288 100644 --- a/src/pages/camera-mixin.js +++ b/src/pages/camera-mixin.js @@ -5,7 +5,6 @@ export default { const devicesList = await navigator.mediaDevices.enumerateDevices() this.videoDeviceAvailable = devicesList.some( d => d.kind == "videoinput") if (this.videoDeviceAvailable) { - navigator.mediaDevices.getUserMedia({video: true}) var vidConstraint = { video: { width: { @@ -37,9 +36,6 @@ export default { const tempCtx = tempCVS.getContext('2d') tempCtx.drawImage(vidViewer, 0, 0) this.getImage(tempCVS.toDataURL()) - }, - async videoStream() { - //TODO } } } \ No newline at end of file diff --git a/src/pages/detect.vue b/src/pages/detect.vue index 33a86c3..ea7a555 100644 --- a/src/pages/detect.vue +++ b/src/pages/detect.vue @@ -6,12 +6,12 @@
- -
+
- Capture + Capture
+
+ @@ -147,7 +148,9 @@ uploadUid: null, uploadDirty: false, modelLocation: '', + miniLocation: '', modelLoading: true, + reloadModel: false, videoDeviceAvailable: false, videoAvailable: false, cameraStream: null @@ -163,17 +166,23 @@ case 'thorax': this.activeRegion = 0 this.detectorName = 'thorax' - //this.classesList = thoraxClasses /* VITE setting */ this.modelLocation = `../models/thorax${this.otherSettings.mini ? '-mini' : ''}/model.json` + this.miniLocation = `../models/thorax-mini/model.json` /* PWA Build setting */ //this.modelLocation = `./models/thorax${this.otherSettings.mini ? '-mini' : ''}/model.json` this.modelLocationCordova = `https://localhost/models/thorax${this.otherSettings.mini ? '-mini' : ''}/model.json` break; case 'abdomen': this.activeRegion = 1 - this.detectorName = 'combined' - break; + this.detectorName = 'abdomen' + /* VITE setting */ + this.modelLocation = `../models/abdomen${this.otherSettings.mini ? '-mini' : ''}/model.json` + this.miniLocation = `../models/abdomen-mini/model.json` + /* PWA Build setting */ + //this.modelLocation = `./models/abdomen${this.otherSettings.mini ? '-mini' : ''}/model.json` + this.modelLocationCordova = `https://localhost/models/abdomen${this.otherSettings.mini ? '-mini' : ''}/model.json` + break; case 'limbs': this.activeRegion = 2 this.detectorName = 'defaultNew' @@ -195,7 +204,7 @@ this.modelLoading = false } else { this.modelLoading = true - this.loadModel(this.isCordova ? this.modelLocationCordova : this.modelLocation).then(() => { + this.loadModel(this.isCordova ? this.modelLocationCordova : this.modelLocation, true).then(() => { this.modelLoading = false }).catch((e) => { console.log(e.message) @@ -253,7 +262,11 @@ chipGradient (confVal) { return `--chip-media-background: hsl(${confVal / 100 * 120}deg 100% 50%)` }, - setData () { + async setData () { + if (this.reloadModel) { + await this.loadModel(this.isCordova ? this.modelLocationCordova : this.modelLocation) + this.reloadModel = false + } if (this.serverSettings && this.serverSettings.use) { this.remoteDetect() } else { @@ -284,7 +297,20 @@ } if (mode == "camera") { this.videoAvailable = await this.openCamera(this.$refs.image_container) - if (this.videoAvailable) { return } + if (this.videoAvailable) { + this.imageLoaded = false + this.imageView = null + this.$refs.image_cvs.style['background-image'] = 'none' + this.resultData = {} + var trackDetails = this.cameraStream.getVideoTracks()[0].getSettings() + var vidElement = this.$refs.vid_viewer + vidElement.width = trackDetails.width + vidElement.height = trackDetails.height + if (!this.otherSettings.disableVideo) { + this.videoFrameDetect(vidElement) + } + return + } } if (mode == 'sample') { f7.dialog.create({ @@ -350,6 +376,7 @@ if (this.videoAvailable) { this.closeCamera() this.detecting = true + this.reloadModel = true resolve(searchImage) } else if (this.isCordova && this.imageLoadMode == "camera") { this.detecting = true @@ -421,7 +448,7 @@ this.selectChip(findBox >= 0 ? this.resultData.detections[findBox].resultIndex : this.selectedChip) }, box2cvs(boxInput) { - if (!boxInput) return [] + if (!boxInput || boxInput.length == 0) return [] const boxList = boxInput.length ? boxInput : [boxInput] const [imCanvas, imageCtx] = this.resetView() var imgWidth diff --git a/src/pages/detection-mixin.js b/src/pages/detection-mixin.js index 46eb871..2dbd615 100644 --- a/src/pages/detection-mixin.js +++ b/src/pages/detection-mixin.js @@ -5,11 +5,23 @@ var model = null export default { methods: { - async loadModel(weights) { + async loadModel(weights, preload) { + if (model && model.modelURL == weights) { + return model + } else if (model) { + model.dispose() + } model = await tf.loadGraphModel(weights) const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3) - const dummyT = tf.ones([1,modelWidth,modelHeight,3]) - model.predict(dummyT) //Run model once to preload weights for better response time + /***************** + * If preloading then run model + * once on fake data to preload + * weights for a faster response + *****************/ + if (preload) { + const dummyT = tf.ones([1,modelWidth,modelHeight,3]) + model.predict(dummyT) + } return model }, async localDetect(imageData) { @@ -150,7 +162,60 @@ export default { remoteTimeout () { this.detecting = false f7.dialog.alert('No connection to remote ALVINN instance. Please check app settings.') - } + }, + async videoFrameDetect (vidData) { + await this.loadModel(this.miniLocation) + const [modelWidth, modelHeight] = model.inputs[0].shape.slice(1, 3) + const imCanvas = this.$refs.image_cvs + const imageCtx = imCanvas.getContext("2d") + const target = this.$refs.target_image + await tf.nextFrame(); + imCanvas.width = imCanvas.clientWidth + imCanvas.height = imCanvas.clientHeight + imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height) + var imgWidth + var imgHeight + const imgAspect = vidData.clientWidth / vidData.clientHeight + const rendAspect = imCanvas.width / imCanvas.height + if (imgAspect >= rendAspect) { + imgWidth = imCanvas.width + imgHeight = imCanvas.width / imgAspect + } else { + imgWidth = imCanvas.height * imgAspect + imgHeight = imCanvas.height + } + while (this.videoAvailable) { + console.time('frame-process') + try { + const input = tf.tidy(() => { + return tf.image.resizeBilinear(tf.browser.fromPixels(vidData), [modelWidth, modelHeight]).div(255.0).expandDims(0) + }) + const res = model.predict(input) + const rawRes = tf.transpose(res,[0,2,1]).arraySync()[0] + let rawCoords = [] + if (rawRes) { + for (var i = 0; i < rawRes.length; i++) { + var getScores = rawRes[i].slice(4) + if (getScores.some( s => s > .5)) { + rawCoords.push(rawRes[i].slice(0,2)) + } + } + + imageCtx.clearRect(0,0,imCanvas.width,imCanvas.height) + for (var coord of rawCoords) { + console.log(`x: ${coord[0]}, y: ${coord[1]}`) + let pointX = (imCanvas.width - imgWidth) / 2 + (coord[0] / modelWidth) * imgWidth -5 + let pointY = (imCanvas.height - imgHeight) / 2 + (coord[1] / modelHeight) * imgHeight -5 + imageCtx.drawImage(target, pointX, pointY, 20, 20) + } + } + } catch (e) { + console.log(e) + } + console.timeEnd('frame-process') + await tf.nextFrame(); + } + } } } \ No newline at end of file diff --git a/src/pages/settings.vue b/src/pages/settings.vue index 5cec503..c249f97 100644 --- a/src/pages/settings.vue +++ b/src/pages/settings.vue @@ -27,6 +27,10 @@ Enable demo mode
+
+ Disable video estimates + +
Use external server diff --git a/src/pages/specs.vue b/src/pages/specs.vue index 8277a26..42fdc7f 100644 --- a/src/pages/specs.vue +++ b/src/pages/specs.vue @@ -13,7 +13,8 @@ - + + @@ -39,7 +40,8 @@ return { thoraxDetails: {}, miniThoraxDetails: {}, - abdomenDetails: { "version": "N/A" }, + abdomenDetails: {}, + miniAbdomenDetails: {}, limbsDetails: { "version": "N/A" }, headneckDetails: { "version": "N/A" }, alvinnVersion: store().getVersion, @@ -60,7 +62,14 @@ .then((mod) => { this.miniThoraxDetails = mod.default }) - + import('../models/abdomen/descript.json') + .then((mod) => { + this.abdomenDetails = mod.default + }) + import('../models/abdomen-mini/descript.json') + .then((mod) => { + this.miniAbdomenDetails = mod.default + }) }, methods: { }