fixed merge conflicts and updated readme

Author: joeyklee

README.md

@@ -31,12 +31,69 @@ python -m http.server
 
 If you don't know how to start a server, check [this](https://github.com/processing/p5.js/wiki/Local-server) guide.
 
+## Examples Index
+
+Below is the current `release` examples index:
+
+### javascript
+
+ml5.js does not require p5.js, however as ml5.js and p5.js have been designed to play nicely with eachother, most of our examples currently are developed together with p5.js. The following "vanilla" javascript examples showcase the use of ml5 without p5.js.
+
+* [FeatureExtractor_Image_Classification](https://ml5js.github.io/ml5-examples/javascript/FeatureExtractor_Image_Classification)
+* [ImageClassification_Video](https://ml5js.github.io/ml5-examples/javascript/ImageClassification_Video)
+* [ImageClassification](https://ml5js.github.io/ml5-examples/javascript/ImageClassification)
+* [StyleTransfer_Image](https://ml5js.github.io/ml5-examples/javascript/StyleTransfer_Image)
+* [PoseNet](https://ml5js.github.io/ml5-examples/javascript/PoseNet)
+
+### p5js
+
+* [CVAE](https://ml5js.github.io/ml5-examples/p5js/CVAE)
+* [BodyPix_Image](https://ml5js.github.io/ml5-examples/p5js/BodyPix/BodyPix_Image)
+* [BodyPix_Webcam](https://ml5js.github.io/ml5-examples/p5js/BodyPix/BodyPix_Webcam)
+* [BodyPix_Webcam_Parts](https://ml5js.github.io/ml5-examples/p5js/BodyPix/BodyPix_Webcam_Parts)
+* [DCGAN](https://ml5js.github.io/ml5-examples/p5js/DCGAN)
+* [Sentiment](https://ml5js.github.io/ml5-examples/p5js/Sentiment)
+* [UNET](https://ml5js.github.io/ml5-examples/p5js/UNET/UNET_webcam)
+* [Word2Vec](https://ml5js.github.io/ml5-examples/p5js/Word2Vec)
+* [FeatureExtractor_Image_Classification](https://ml5js.github.io/ml5-examples/p5js/FeatureExtractor/FeatureExtractor_Image_Classification)
+* [FeatureExtractor_Image_Regression](https://ml5js.github.io/ml5-examples/p5js/FeatureExtractor/FeatureExtractor_Image_Regression)
+* [StyleTransfer_Video](https://ml5js.github.io/ml5-examples/p5js/StyleTransfer/StyleTransfer_Video)
+* [StyleTransfer_Image](https://ml5js.github.io/ml5-examples/p5js/StyleTransfer/StyleTransfer_Image)
+* [ImageClassification_Video](https://ml5js.github.io/ml5-examples/p5js/ImageClassification/ImageClassification_Video)
+* [ImageClassification_VideoScavengerHunt](https://ml5js.github.io/ml5-examples/p5js/ImageClassification/ImageClassification_VideoScavengerHunt)
+* [ImageClassification](https://ml5js.github.io/ml5-examples/p5js/ImageClassification/ImageClassification)
+* [ImageClassification_VideoSoundTranslate](https://ml5js.github.io/ml5-examples/p5js/ImageClassification/ImageClassification_VideoSoundTranslate)
+* [ImageClassification_VideoSound](https://ml5js.github.io/ml5-examples/p5js/ImageClassification/ImageClassification_VideoSound)
+* [ImageClassification_MultipleImages](https://ml5js.github.io/ml5-examples/p5js/ImageClassification/ImageClassification_MultipleImages)
+* [KNNClassification_VideoSound](https://ml5js.github.io/ml5-examples/p5js/KNNClassification/KNNClassification_VideoSound)
+* [KNNClassification_Video](https://ml5js.github.io/ml5-examples/p5js/KNNClassification/KNNClassification_Video)
+* [KNNClassification_PoseNet](https://ml5js.github.io/ml5-examples/p5js/KNNClassification/KNNClassification_PoseNet)
+* [KNNClassification_VideoSquare](https://ml5js.github.io/ml5-examples/p5js/KNNClassification/KNNClassification_VideoSquare)
+* [SketchRNN_basic](https://ml5js.github.io/ml5-examples/p5js/SketchRNN/SketchRNN_basic)
+* [SketchRNN_interactive](https://ml5js.github.io/ml5-examples/p5js/SketchRNN/SketchRNN_interactive)
+* [PitchDetection_Game](https://ml5js.github.io/ml5-examples/p5js/PitchDetection/PitchDetection_Game)
+* [PitchDetection](https://ml5js.github.io/ml5-examples/p5js/PitchDetection/PitchDetection)
+* [CharRNN_Interactive](https://ml5js.github.io/ml5-examples/p5js/CharRNN/CharRNN_Interactive)
+* [CharRNN_Text](https://ml5js.github.io/ml5-examples/p5js/CharRNN/CharRNN_Text)
+* [CharRNN_Text_Stateful](https://ml5js.github.io/ml5-examples/p5js/CharRNN/CharRNN_Text_Stateful)
+* [Pix2Pix_callback](https://ml5js.github.io/ml5-examples/p5js/Pix2Pix/Pix2Pix_callback)
+* [Pix2Pix_promise](https://ml5js.github.io/ml5-examples/p5js/Pix2Pix/Pix2Pix_promise)
+* [YOLO_webcam](https://ml5js.github.io/ml5-examples/p5js/YOLO/YOLO_webcam)
+* [YOLO_single_image](https://ml5js.github.io/ml5-examples/p5js/YOLO/YOLO_single_image)
+* [images](https://ml5js.github.io/ml5-examples/p5js/YOLO/YOLO_single_image/images)
+* [PoseNet_image_single](https://ml5js.github.io/ml5-examples/p5js/PoseNet/PoseNet_image_single)
+* [data](https://ml5js.github.io/ml5-examples/p5js/PoseNet/PoseNet_image_single/data)
+* [PoseNet_webcam](https://ml5js.github.io/ml5-examples/p5js/PoseNet/PoseNet_webcam)
+* [PoseNet_part_selection](https://ml5js.github.io/ml5-examples/p5js/PoseNet/PoseNet_part_selection)
+
 ## p5.js web editor examples
 
 The p5.js examples can also be run using the [p5.js web editor](https://alpha.editor.p5js.org). We are [in the process of porting](https://github.com/ml5js/ml5-examples/issues/6) and would welcome any contributions!
 
-* [PoseNet Example](https://alpha.editor.p5js.org/ml5/sketches/B1uDXDugX)
-* [YOLO Example](https://alpha.editor.p5js.org/ml5/sketches/HyKg7DOe7)
+You can find all of our examples here:
+* [ml5 on editor.p5js.org](https://editor.p5js.org/ml5/sketches)
+
+NOTE: not all of the ml5.js examples are currently working on the p5.js web editor. Stay tuned for updates!
 
 ## Contributing
 

p5js/DCGAN/model/group1-shard1of4

@@ -0,0 +1 @@
+{"modelTopology": {"keras_version": "2.2.2", "backend": "tensorflow", "model_config": {"class_name": "Sequential", "config": [{"class_name": "Dense", "config": {"name": "dense_2", "trainable": true, "batch_input_shape": [null, 128], "dtype": "float32", "units": 8192, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"scale": 1.0, "mode": "fan_avg", "distribution": "uniform", "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}}, {"class_name": "BatchNormalization", "config": {"name": "batch_normalization_5", "trainable": true, "axis": 1, "momentum": 0.99, "epsilon": 0.001, "center": true, "scale": true, "beta_initializer": {"class_name": "Zeros", "config": {}}, "gamma_initializer": {"class_name": "Ones", "config": {}}, "moving_mean_initializer": {"class_name": "Zeros", "config": {}}, "moving_variance_initializer": {"class_name": "Ones", "config": {}}, "beta_regularizer": null, "gamma_regularizer": null, "beta_constraint": null, "gamma_constraint": null}}, {"class_name": "Activation", "config": {"name": "activation_6", "trainable": true, "activation": "relu"}}, {"class_name": "Reshape", "config": {"name": "reshape_2", "trainable": true, "target_shape": [512, 4, 4]}}, {"class_name": "Conv2DTranspose", "config": {"name": "conv2d_transpose_5", "trainable": true, "filters": 256, "kernel_size": [4, 4], "strides": [2, 2], "padding": "same", "data_format": "channels_first", "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"scale": 1.0, "mode": "fan_avg", "distribution": "uniform", "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null, "output_padding": null}}, {"class_name": "BatchNormalization", "config": {"name": "batch_normalization_6", "trainable": true, "axis": 1, "momentum": 0.99, "epsilon": 0.001, "center": true, "scale": true, "beta_initializer": {"class_name": "Zeros", "config": {}}, "gamma_initializer": {"class_name": "Ones", "config": {}}, "moving_mean_initializer": {"class_name": "Zeros", "config": {}}, "moving_variance_initializer": {"class_name": "Ones", "config": {}}, "beta_regularizer": null, "gamma_regularizer": null, "beta_constraint": null, "gamma_constraint": null}}, {"class_name": "Activation", "config": {"name": "activation_7", "trainable": true, "activation": "relu"}}, {"class_name": "Conv2DTranspose", "config": {"name": "conv2d_transpose_6", "trainable": true, "filters": 128, "kernel_size": [4, 4], "strides": [2, 2], "padding": "same", "data_format": "channels_first", "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"scale": 1.0, "mode": "fan_avg", "distribution": "uniform", "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null, "output_padding": null}}, {"class_name": "BatchNormalization", "config": {"name": "batch_normalization_7", "trainable": true, "axis": 1, "momentum": 0.99, "epsilon": 0.001, "center": true, "scale": true, "beta_initializer": {"class_name": "Zeros", "config": {}}, "gamma_initializer": {"class_name": "Ones", "config": {}}, "moving_mean_initializer": {"class_name": "Zeros", "config": {}}, "moving_variance_initializer": {"class_name": "Ones", "config": {}}, "beta_regularizer": null, "gamma_regularizer": null, "beta_constraint": null, "gamma_constraint": null}}, {"class_name": "Activation", "config": {"name": "activation_8", "trainable": true, "activation": "relu"}}, {"class_name": "Conv2DTranspose", "config": {"name": "conv2d_transpose_7", "trainable": true, "filters": 64, "kernel_size": [4, 4], "strides": [2, 2], "padding": "same", "data_format": "channels_first", "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"scale": 1.0, "mode": "fan_avg", "distribution": "uniform", "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null, "output_padding": null}}, {"class_name": "BatchNormalization", "config": {"name": "batch_normalization_8", "trainable": true, "axis": 1, "momentum": 0.99, "epsilon": 0.001, "center": true, "scale": true, "beta_initializer": {"class_name": "Zeros", "config": {}}, "gamma_initializer": {"class_name": "Ones", "config": {}}, "moving_mean_initializer": {"class_name": "Zeros", "config": {}}, "moving_variance_initializer": {"class_name": "Ones", "config": {}}, "beta_regularizer": null, "gamma_regularizer": null, "beta_constraint": null, "gamma_constraint": null}}, {"class_name": "Activation", "config": {"name": "activation_9", "trainable": true, "activation": "relu"}}, {"class_name": "Conv2DTranspose", "config": {"name": "conv2d_transpose_8", "trainable": true, "filters": 3, "kernel_size": [4, 4], "strides": [2, 2], "padding": "same", "data_format": "channels_first", "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"scale": 1.0, "mode": "fan_avg", "distribution": "uniform", "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null, "output_padding": null}}, {"class_name": "Activation", "config": {"name": "activation_10", "trainable": true, "activation": "tanh"}}]}}, "weightsManifest": [{"paths": ["group1-shard1of4", "group1-shard2of4", "group1-shard3of4", "group1-shard4of4"], "weights": [{"name": "batch_normalization_5/gamma", "shape": [8192], "dtype": "float32"}, {"name": "batch_normalization_5/beta", "shape": [8192], "dtype": "float32"}, {"name": "batch_normalization_5/moving_mean", "shape": [8192], "dtype": "float32"}, {"name": "batch_normalization_5/moving_variance", "shape": [8192], "dtype": "float32"}, {"name": "batch_normalization_6/gamma", "shape": [256], "dtype": "float32"}, {"name": "batch_normalization_6/beta", "shape": [256], "dtype": "float32"}, {"name": "batch_normalization_6/moving_mean", "shape": [256], "dtype": "float32"}, {"name": "batch_normalization_6/moving_variance", "shape": [256], "dtype": "float32"}, {"name": "batch_normalization_7/gamma", "shape": [128], "dtype": "float32"}, {"name": "batch_normalization_7/beta", "shape": [128], "dtype": "float32"}, {"name": "batch_normalization_7/moving_mean", "shape": [128], "dtype": "float32"}, {"name": "batch_normalization_7/moving_variance", "shape": [128], "dtype": "float32"}, {"name": "batch_normalization_8/gamma", "shape": [64], "dtype": "float32"}, {"name": "batch_normalization_8/beta", "shape": [64], "dtype": "float32"}, {"name": "batch_normalization_8/moving_mean", "shape": [64], "dtype": "float32"}, {"name": "batch_normalization_8/moving_variance", "shape": [64], "dtype": "float32"}, {"name": "conv2d_transpose_5/kernel", "shape": [4, 4, 256, 512], "dtype": "float32"}, {"name": "conv2d_transpose_5/bias", "shape": [256], "dtype": "float32"}, {"name": "conv2d_transpose_6/kernel", "shape": [4, 4, 128, 256], "dtype": "float32"}, {"name": "conv2d_transpose_6/bias", "shape": [128], "dtype": "float32"}, {"name": "conv2d_transpose_7/kernel", "shape": [4, 4, 64, 128], "dtype": "float32"}, {"name": "conv2d_transpose_7/bias", "shape": [64], "dtype": "float32"}, {"name": "conv2d_transpose_8/kernel", "shape": [4, 4, 3, 64], "dtype": "float32"}, {"name": "conv2d_transpose_8/bias", "shape": [3], "dtype": "float32"}, {"name": "dense_2/kernel", "shape": [128, 8192], "dtype": "float32"}, {"name": "dense_2/bias", "shape": [8192], "dtype": "float32"}]}]}

p5js/DCGAN/model/group1-shard2of4

@@ -38,4 +38,4 @@ function displayImage(err, result) {
     return;
   }
   image(result.image, 0, 0, 200, 200);
-}
+}

p5js/DCGAN/model/group1-shard3of4

@@ -33,4 +33,4 @@ <h1>Image Classification using Feature Extractor with MobileNet</h1>
     </p>
     <script src="sketch.js"></script>
   </body>
-</html>
+</html>