adding compiler and improving main_program code

app.py

@@ -9,7 +9,7 @@ def model_interface(image):
 
 # main method that call the main_program where code is generated and then compiled
 def main_model(input_image):
-    result = main_program.main_program(input_image)
+    result = main_program.main_method(input_image)
     return result
 
 
@@ -25,8 +25,8 @@ developing the structures of a web pages.</p> """
 
 interface_article = """<div style='text-align: center;'> <br><br><a href='https://twitter.com/taneemishere' 
 target='_blank'>Developed by Taneem Jan</a> </div> 
-<div style='text-align: center;'> <a href='https://taneemishere.github.io' 
-target='_blank'>Paper</a> &ensp; &emsp; <a href='https://github.com/taneemishere' 
+<div style='text-align: center;'> <a href='https://taneemishere.github.io/projects/project-one.html' 
+target='_blank'>Paper</a> &ensp; &emsp; <a href='https://github.com/taneemishere/html-code-generation-from-images-with-deep-neural-networks' 
 target='_blank'>Code</a> </div>
 """
 

bin/meta_dataset.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3327bd2481728a5d7306c51a057ae24a98aaf80a6f2a042b23c6af5e23d1a327
+size 294

classes/Sampler.py

@@ -3,7 +3,6 @@ from __future__ import absolute_import
 __author__ = 'Tony Beltramelli - www.tonybeltramelli.com'
 
 from .Vocabulary import *
-# from .BeamSearch import *
 from .Utils import *
 
 
@@ -58,59 +57,3 @@ class Sampler:
 
         return predictions, out_probas
 
-    # def recursive_beam_search(self, model, input_img, current_context, beam, current_node, sequence_length):
-    #     probas = model.predict(input_img, np.array([current_context]))
-
-    #     predictions = []
-    #     for i in range(0, len(probas)):
-    #         predictions.append((i, probas[i], probas))
-
-    #     nodes = []
-    #     for i in range(0, len(predictions)):
-    #         prediction = predictions[i][0]
-    #         score = predictions[i][1]
-    #         output_probas = predictions[i][2]
-    #         nodes.append(Node(prediction, score, output_probas))
-
-    #     beam.add_nodes(current_node, nodes)
-
-    #     if beam.is_valid():
-    #         beam.prune_leaves()
-    #         if sequence_length == 1 or self.voc.token_lookup[beam.root.max_child().key] == END_TOKEN:
-    #             return
-
-    #         for node in beam.get_leaves():
-    #             prediction = node.key
-
-    #             new_context = []
-    #             for j in range(1, self.context_length):
-    #                 new_context.append(current_context[j])
-    #             sparse_label = np.zeros(self.output_size)
-    #             sparse_label[prediction] = 1
-    #             new_context.append(sparse_label)
-
-    #             self.recursive_beam_search(model, input_img, new_context, beam, node, sequence_length - 1)
-
-    # def predict_beam_search(self, model, input_img, beam_width=3, require_sparse_label=True, sequence_length=150):
-    #     predictions = START_TOKEN
-    #     out_probas = []
-
-    #     current_context = [self.voc.vocabulary[PLACEHOLDER]] * (self.context_length - 1)
-    #     current_context.append(self.voc.vocabulary[START_TOKEN])
-    #     if require_sparse_label:
-    #         current_context = Utils.sparsify(current_context, self.output_size)
-
-    #     beam = BeamSearch(beam_width=beam_width)
-
-    #     self.recursive_beam_search(model, input_img, current_context, beam, beam.root, sequence_length)
-
-    #     predicted_sequence, probas_sequence = beam.search()
-
-    #     for k in range(0, len(predicted_sequence)):
-    #         prediction = predicted_sequence[k]
-    #         probas = probas_sequence[k]
-    #         out_probas.append(probas)
-
-    #         predictions += self.voc.token_lookup[prediction]
-
-    #     return predictions, out_probas

classes/model/pix2code2.py

@@ -2,7 +2,6 @@ __author__ = 'Ferdiand John Briones, attempt at pix2code2 through pretrained aut
 
 from keras.layers import Input, Dense, Dropout, RepeatVector, LSTM, concatenate, Flatten
 from keras.models import Sequential, Model
-# from keras.optimizers import RMSprop
 from tensorflow.keras.optimizers import RMSprop
 from keras import *
 from .Config import *

compiler/Compiler.py

@@ -0,0 +1,44 @@
+#!/usr/bin/env python
+__author__ = 'Tony Beltramelli - www.tonybeltramelli.com'
+
+import json
+from compiler.Node import *
+
+
+class Compiler:
+    def __init__(self, dsl_mapping_file_path):
+        with open(dsl_mapping_file_path) as data_file:
+            self.dsl_mapping = json.load(data_file)
+
+        self.opening_tag = self.dsl_mapping["opening-tag"]
+        self.closing_tag = self.dsl_mapping["closing-tag"]
+        self.content_holder = self.opening_tag + self.closing_tag
+
+        self.root = Node("body", None, self.content_holder)
+
+    def compile(self, input_file_path, output_file_path, rendering_function=None):
+        dsl_file = open(input_file_path)
+        current_parent = self.root
+
+        for token in dsl_file:
+            token = token.replace(" ", "").replace("\n", "")
+
+            if token.find(self.opening_tag) != -1:
+                token = token.replace(self.opening_tag, "")
+
+                element = Node(token, current_parent, self.content_holder)
+                current_parent.add_child(element)
+                current_parent = element
+            elif token.find(self.closing_tag) != -1:
+                current_parent = current_parent.parent
+            else:
+                tokens = token.split(",")
+                for t in tokens:
+                    element = Node(t, current_parent, self.content_holder)
+                    current_parent.add_child(element)
+
+        output_html = self.root.render(self.dsl_mapping, rendering_function=rendering_function)
+        with open(output_file_path, 'w') as output_file:
+            output_file.write(output_html)
+
+        return output_html

compiler/Node.py

@@ -0,0 +1,33 @@
+#!/usr/bin/env python
+from __future__ import print_function
+__author__ = 'Tony Beltramelli - www.tonybeltramelli.com'
+
+
+class Node:
+    def __init__(self, key, parent_node, content_holder):
+        self.key = key
+        self.parent = parent_node
+        self.children = []
+        self.content_holder = content_holder
+
+    def add_child(self, child):
+        self.children.append(child)
+
+    def show(self):
+        print(self.key)
+        for child in self.children:
+            child.show()
+
+    def render(self, mapping, rendering_function=None):
+        content = ""
+        for child in self.children:
+            content += child.render(mapping, rendering_function)
+
+        value = mapping[self.key]
+        if rendering_function is not None:
+            value = rendering_function(self.key, value)
+
+        if len(self.children) != 0:
+            value = value.replace(self.content_holder, content)
+
+        return value

compiler/Utils.py

@@ -0,0 +1,51 @@
+__author__ = 'Tony Beltramelli - www.tonybeltramelli.com'
+
+import string
+import random
+
+
+class Utils:
+    @staticmethod
+    def get_random_text(length_text=10, space_number=1, with_upper_case=True):
+        results = []
+        while len(results) < length_text:
+            char = random.choice(string.ascii_letters[:26])
+            results.append(char)
+        if with_upper_case:
+            results[0] = results[0].upper()
+
+        current_spaces = []
+        while len(current_spaces) < space_number:
+            space_pos = random.randint(2, length_text - 3)
+            if space_pos in current_spaces:
+                break
+            results[space_pos] = " "
+            if with_upper_case:
+                results[space_pos + 1] = results[space_pos - 1].upper()
+
+            current_spaces.append(space_pos)
+
+        return ''.join(results)
+
+    @staticmethod
+    def get_ios_id(length=10):
+        results = []
+
+        while len(results) < length:
+            char = random.choice(string.digits + string.ascii_letters)
+            results.append(char)
+
+        results[3] = "-"
+        results[6] = "-"
+
+        return ''.join(results)
+
+    @staticmethod
+    def get_android_id(length=10):
+        results = []
+
+        while len(results) < length:
+            char = random.choice(string.ascii_letters)
+            results.append(char)
+
+        return ''.join(results)

compiler/assets/web-dsl-mapping.json

@@ -0,0 +1,18 @@
+{
+  "opening-tag": "{",
+  "closing-tag": "}",
+  "body": "<html>\n  <header>\n    <meta charset=\"utf-8\">\n    <meta name=\"viewport\" content=\"width=device-width, initial-scale=1\">\n    <link rel=\"stylesheet\" href=\"https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css\" integrity=\"sha384-BVYiiSIFeK1dGmJRAkycuHAHRg32OmUcww7on3RYdg4Va+PmSTsz/K68vbdEjh4u\" crossorigin=\"anonymous\">\n<link rel=\"stylesheet\" href=\"https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap-theme.min.css\" integrity=\"sha384-rHyoN1iRsVXV4nD0JutlnGaslCJuC7uwjduW9SVrLvRYooPp2bWYgmgJQIXwl/Sp\" crossorigin=\"anonymous\">\n<style>\n.header{margin:20px 0}nav ul.nav-pills li{background-color:#333;border-radius:4px;margin-right:10px}.col-lg-3{width:24%;margin-right:1.333333%}.col-lg-6{width:49%;margin-right:2%}.col-lg-12,.col-lg-3,.col-lg-6{margin-bottom:20px;border-radius:6px;background-color:#f5f5f5;padding:20px}.row .col-lg-3:last-child,.row .col-lg-6:last-child{margin-right:0}footer{padding:20px 0;text-align:center;border-top:1px solid #bbb}\n</style>\n    <title>Scaffold</title>\n  </header>\n  <body>\n    <main class=\"container\">\n      {}\n      <footer class=\"footer\">\n        <p>&copy; Tony Beltramelli 2017</p>\n      </footer>\n    </main>\n    <script src=\"js/jquery.min.js\"></script>\n    <script src=\"js/bootstrap.min.js\"></script>\n  </body>\n</html>\n",
+  "header": "<div class=\"header clearfix\">\n  <nav>\n    <ul class=\"nav nav-pills pull-left\">\n      {}\n    </ul>\n  </nav>\n</div>\n",
+  "btn-active": "<li class=\"active\"><a href=\"#\">[]</a></li>\n",
+  "btn-inactive": "<li><a href=\"#\">[]</a></li>\n",
+  "row": "<div class=\"row\">{}</div>\n",
+  "single": "<div class=\"col-lg-12\">\n{}\n</div>\n",
+  "double": "<div class=\"col-lg-6\">\n{}\n</div>\n",
+  "quadruple": "<div class=\"col-lg-3\">\n{}\n</div>\n",
+  "btn-green": "<a class=\"btn btn-success\" href=\"#\" role=\"button\">[]</a>\n",
+  "btn-orange": "<a class=\"btn btn-warning\" href=\"#\" role=\"button\">[]</a>\n",
+  "btn-red": "<a class=\"btn btn-danger\" href=\"#\" role=\"button\">[]</a>",
+  "big-title": "<h2>[]</h2>",
+  "small-title": "<h4>[]</h4>",
+  "text": "<p>[]</p>\n"
+}

main_program.py

@@ -8,18 +8,10 @@ from classes.Sampler import *
 from classes.model.pix2code2 import *
 
 
-def code_gen(path_to_input_image):
-    # if len(sys.argv) < 1:
-    #     print("Error: not enough argument supplied:")
-    #     # print( "sample.py <trained weights path> <trained model name> <input image> <output path> <search method (
-    #     # default: " "greedy)>")
-    #     exit(0)
-    # else:
+def dsl_code_geneneration(input_image):
     trained_weights_path = "../bin"
     trained_model_name = "pix2code2"
-    # input_path = sys.argv[1]
-    # input_path = "../data/test_gu.png"
-    input_path = path_to_input_image
+    input_path = input_image
     output_path = "../data/output/"
     search_method = "greedy"
 
@@ -39,12 +31,7 @@ def code_gen(path_to_input_image):
     if search_method == "greedy":
         result, _ = sampler.predict_greedy(model, np.array([evaluation_img]))
         print("Result greedy: \n {}".format(result))
-    # else:
-    #     beam_width = int(search_method)
-    #     print("Search with beam width: {}".format(beam_width))
-    #     result, _ = sampler.predict_beam_search(model, np.array([evaluation_img]), beam_width=beam_width)
-    #     print("Result beam: {}".format(result))
-
+    
     with open("{}/{}.gui".format(output_path, file_name), 'w') as out_f:
         out_f.write(result.replace(START_TOKEN, "").replace(END_TOKEN, ""))
 
@@ -70,7 +57,7 @@ def compile_gui(outputpath, filename):
     FILL_WITH_RANDOM_TEXT = True
     TEXT_PLACE_HOLDER = "[]"
 
-    dsl_path = "assets/web-dsl-mapping.json"
+    dsl_path = "compiler/assets/web-dsl-mapping.json"
     compiler = Compiler(dsl_path)
 
     def render_content_with_text(key, value):
@@ -95,7 +82,7 @@ def compile_gui(outputpath, filename):
     return html_code
 
 
-def main_program(path_to_file):
-    output_path, file_name = code_gen(path_to_file)
+def main_method(input_image_from_interface):
+    output_path, file_name = dsl_code_geneneration(input_image_from_interface)
     result = compile_gui(output_path, file_name)
     return result