mini_cocopi/python/blockly/generators/python/visionkit.js

/**
 * @license
 * Visual Blocks Language
 *
 * Copyright 2012 Google Inc.
 * https://developers.google.com/blockly/
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

/**
 * @fileoverview Generating Python for colour blocks.
 * @author fraser@google.com (Neil Fraser)
 */
'use strict';

goog.provide('Blockly.Python.visionkit');

goog.require('Blockly.Python');

Blockly.Python["visionkit_import"] =  function(block) {
    var vision_import = Blockly.Python.valueToCode(block,"IMPORT",Blockly.Python.ORDER_NONE) || 0;
    var vision_from = block.getFieldValue("FROM");
    var code = "from " + vision_from + " " + vision_import+ "\n";
    return code;
}

Blockly.Python["visionkit_import_annotator"] = function(block) {
    var code ="import " + block.getFieldValue("IMPORT") || "Annotator"
    return [code, Blockly.Python.ORDER_ATOMIC];
}

Blockly.Python["visionkit_import_models"] = function(block) {
    var code ="import "+ block.getFieldValue("IMPORT") || "face_detection"
    return [code, Blockly.Python.ORDER_ATOMIC];
}

Blockly.Python["visionkit_import_inference"] = function(block) {
    var code ="import "+ block.getFieldValue("IMPORT") || "CameraInference"
    return [code, Blockly.Python.ORDER_ATOMIC];
}

Blockly.Python["visionkit_cameraInference"] = function(block) {
    var inference = block.getFieldValue("INFERENCE");
    var usemodel = block.getFieldValue("USEMODEL");
    var statement_input = Blockly.Python.statementToCode(block, "STACK");
    var code = "with CameraInference(" + usemodel + ") as " +inference +":\n"+
            statement_input+"\n";
    return code;
}

Blockly.Python["visionkit_runInference"] = function(block) {
    var input = Blockly.Python.valueToCode(block,"INPUT",Blockly.Python.ORDER_NONE) || "";
    var code = "inference.run(" + input + ")";
    return [code, Blockly.Python.ORDER_ATOMIC];
}

Blockly.Python["visionkit_GetInference"] = function(block) {
    var inference = block.getFieldValue("INFERENCE");
    var code = "inference."+ inference;
    return [code, Blockly.Python.ORDER_ATOMIC]; 
}

Blockly.Python["visionkit_faceDetection_operation"] = function(block) {
    var model = block.getFieldValue("MODEL");
    var operation = block.getFieldValue("OPERATION");
    var input = Blockly.Python.valueToCode(block,"INPUT",Blockly.Python.ORDER_NONE) || "";
    var code = model+"."+operation+"("+input+")";
    return [code, Blockly.Python.ORDER_ATOMIC]; 
}

Blockly.Python["visionkit_model_get"] = function(block) {
    var model = block.getFieldValue("MODEL");
    var input = Blockly.Python.valueToCode(block,"INPUT",Blockly.Python.ORDER_NONE) || "";
    var code = input + "." +model;
    return [code, Blockly.Python.ORDER_ATOMIC]; 
}

Blockly.Python['visionkit_Use_Annotator'] = function(block) {
    var annotator = block.getFieldValue("ANNOTATOR");
    var dimen_x = block.getFieldValue("X-DIMEN");
    var dimen_y = block.getFieldValue("Y-DIMEN");
    var code = "Annotator(" + annotator + ", dimensions = ("+ dimen_x + "," + dimen_y +"))\n";
    return code;
}


Blockly.Python['visionkit_Use_Annotator_output'] = function(block) {
    var annotator = block.getFieldValue("ANNOTATOR");
    var dimen_x = block.getFieldValue("X-DIMEN");
    var dimen_y = block.getFieldValue("Y-DIMEN");
    var code = "Annotator(" + annotator + ", dimensions = ("+ dimen_x + "," + dimen_y +"))";
    return [code, Blockly.Python.ORDER_ATOMIC];
}

Blockly.Python['visionkit_Annotator_operation'] = function(block) {
    var operation = block.getFieldValue("OPERATION");
    var code = "annotator." + operation + "()\n";
    return code

} 

Blockly.Python['visionkit_Annotator_Bounding'] = function(block) {
    var fill = block.getFieldValue("FILL")
    var input = Blockly.Python.valueToCode(block,"INPUT",Blockly.Python.ORDER_NONE) || "";
    var code = "annotator.bounding_box(transform(" + input + "),fill="+ fill +")\n";
    return code
} 

Blockly.Python['visionkit_myAssistant'] = function(block) {
    var code = "MyAssistant()";
    return [code, Blockly.Python.ORDER_ATOMIC]
} 






/************************************
*           Simplify                *
*************************************/
Blockly.Python['visionkit_import_aiy'] = function(block) {
    var code = "from aiy.vision.inference import CameraInference\n"+
        "from aiy.vision.models import face_detection\n"+
        "from aiy.vision.annotator import Annotator\n";
    return code;
}

Blockly.Python['visionkit_avg_joy_score'] = function(block) {
    // var input = Blockly.Python.valueToCode(block,"INPUT",Blockly.Python.ORDER_NONE) || "";
    var code = "def avg_joy_score(faces):\n"+
        "    if faces:\n"+
        "        return sum(face.joy_score for face in faces) / len(faces)\n"+
        "    return 0\n";
    return code
}

Blockly.Python['visionkit_annotator_camera'] = function(block) {
    var x = block.getFieldValue("X");
    var y = block.getFieldValue("Y")
    var scale_x = block.getFieldValue("SCALE_X")
    var scale_y = block.getFieldValue("SCALE_Y")
    var code = "annotator = Annotator(camera, dimensions=("+x+", "+y+"))\n"+
        "scale_x = "+x+" / "+scale_x+"\n"+
        "scale_y = "+y+" / "+scale_y+"\n"
    return code;
}

Blockly.Python['visionkit_transform_boundingBox'] = function(block) {
    var code = "def transform(bounding_box):\n"+
        "    x, y, width, height = bounding_box\n"+
        "    return (scale_x * x, scale_y * y, scale_x * (x + width), scale_y * (y + height))\n"
    return code;
}

Blockly.Python['visionkit_CameraInference'] = function(block) {
    var setting = block.getFieldValue("SETTING")
    var statement_input = Blockly.Python.statementToCode(block,"STACK")
    var input_a = Blockly.Python.prefixLines(/** @type {string} */ (statement_input), Blockly.Python.INDENT);
    var code = "with CameraInference(face_detection.model()) as inference:\n"+
        "    for result in inference.run(num_frames):\n"+
        "        faces = face_detection.get_faces(result)\n"+
        "        annotator.clear()\n"+
        "        for face in faces:\n"+
        "            annotator.bounding_box(transform(face.bounding_box), fill=0)\n"+
        "        annotator.update()\n"+
        input_a;
    return code;
    
}

Blockly.Python['visionkit_avg_joy_score_num'] = function(block) {
    var face = block.getFieldValue("FACE")
    var code = "avg_joy_score("+face+")"
    return [code, Blockly.Python.ORDER_ATOMIC]
}

Blockly.Python['visionkit_face'] = function(block) {
    var code = "faces"
    return [code, Blockly.Python.ORDER_ATOMIC]
}