Added worker, fixed microphone error and added work limited search

src/MAGIST/NLP/AudioTranscriber.py

@@ -19,10 +19,6 @@ def __init__(self, config):
 		:param config: The config file(config.json).
 		"""
 
-		self.log = MainLogger(config).StandardLogger("GoogleAudioTranscriber")
-		self.r = sr.Recognizer()
-		self.m = sr.Microphone()
-
 		root_log = MainLogger(config)
 		self.log = root_log.StandardLogger("GoogleAudioTranscriber")  # Create a script specific logging instance
 
@@ -34,6 +30,9 @@ def microphone_listener(self):
 		:return: The transcription of the audio as a string.
 		"""
 
+		self.r = sr.Recognizer()
+		self.m = sr.Microphone()
+
 		with self.m as source:
 			self.log.info("GoogleAudioTranscriber Listening...")
 			audio = self.r.listen(source)
@@ -56,6 +55,10 @@ def file_transcriber(self, file):
 
 		:return: The transcription of the audio as a string.
 		"""
+
+		self.r = sr.Recognizer()
+		self.m = sr.Microphone()
+
 		file = pathlib.Path(file)
 		file = file.resolve()  # Find absolute path from a relative one.
 		file = str(file)
@@ -76,6 +79,4 @@ def file_transcriber(self, file):
 
 			self.log.info("Time taken: " + str(end - start))
 
-		return transcription
-
-
+		return transcription

src/MAGIST/NeuralDB/PrimaryNeuralDB.py

@@ -7,6 +7,7 @@
 import json
 import pathlib
 import time
+import re
 
 from ..Utils.LogMaster.log_init import MainLogger
 
@@ -34,7 +35,6 @@ def __init__(self, config, db_client):
 				self.db_string = i["db_search_zone"]
 			except KeyError:
 				pass
-		print(self.db_string)
 
 	def recreate_db(self):
 		"""Recreate the databases and collections
@@ -47,6 +47,8 @@ def recreate_db(self):
 			time.sleep(1)
 		self.log.warning("Resetting and recreating all databases and tables...")
 
+		self.dbs = []
+
 		for d in self.db_string:
 			if d == "vision":
 				self.vision = self.client['VisionDB']
@@ -57,20 +59,26 @@ def recreate_db(self):
 				self.obj_users = self.vision["ObjectUsers"]
 
 				self.log.info("Vision database is included in NeuralDB search.")
+
+				self.dbs.append(self.vision)
 			if d == "nlp":
 				self.nlp = self.client["NLP"]
 
 				self.word_desc = self.nlp["WordDesc"]
 				self.word_location = self.nlp["WordLocation"]
 
 				self.log.info("NLP database is included in NeuralDB search.")
+
+				self.dbs.append(self.nlp)
 			if d == "common":
 				self.common = self.client["Common"]
 
 				self.word_obj_relation = self.common["WordObjectRelation"]
 
 				self.log.info("Common database is included in NeuralDB search.")
 
+				self.dbs.append(self.common)
+
 		try:
 			if self.vision is None:
 				self.log.warning("Vision database was not included from NeuralDB search.")
@@ -169,7 +177,7 @@ def search_obj_details(self, obj_name):
 
 			for i in d.list_collection_names():
 				self.log.info(f"    ===> Collection: {i}")
-				for j in self.vision[i].find({"obj_name": {"$regex": obj_name}}):
+				for j in self.vision[i].find({"obj_name": re.compile(rf"\b{obj_name}\b", re.IGNORECASE)}):
 					self.log.info(f"        ===> {j}")
 					data.append(j)
 		return data
@@ -190,7 +198,7 @@ def search_obj_desc(self, keyword):
 
 			for i in d.list_collection_names():
 				self.log.info(f"    ===> Collection: {i}")
-				for j in self.vision[i].find({"obj_desc" : {"$regex" : keyword}}):
+				for j in self.vision[i].find({"obj_desc" : re.compile(rf"\b{keyword}\b", re.IGNORECASE)}):
 					self.log.info(f"        ===> {j}")
 					data.append(j)
 		return data
@@ -211,7 +219,7 @@ def search_obj_location(self, location):
 
 			for i in d.list_collection_names():
 				self.log.info(f"    ===> Collection: {i}")
-				for j in self.vision[i].find({"obj_location" : {"$regex" : location}}):
+				for j in self.vision[i].find({"obj_location" : re.compile(rf"\b{location}\b", re.IGNORECASE)}):
 					self.log.info(f"        ===> {j}")
 					data.append(j)
 		return data
@@ -232,7 +240,7 @@ def search_obj_user(self, user):
 
 			for i in d.list_collection_names():
 				self.log.info(f"    ===> Collection: {i}")
-				for j in self.vision[i].find({"user_name" : {"$regex" : user}}):
+				for j in self.vision[i].find({"user_name" : re.compile(rf"\b{user}\b", re.IGNORECASE)}):
 					self.log.info(f"        ===> {j}")
 					data.append(j)
 		return data
@@ -257,7 +265,7 @@ def search_word_details(self, word):
 
 			for i in d.list_collection_names():
 				self.log.info(f"    ===> Collection: {i}")
-				for j in self.vision[i].find({"word_name" : {"$regex" : word}}):
+				for j in self.vision[i].find({"word_name" : re.compile(rf"\b{word}\b", re.IGNORECASE)}):
 					self.log.info(f"        ===> {j}")
 					data.append(j)
 		return data
@@ -278,7 +286,7 @@ def search_word_desc(self, keyword):
 
 			for i in d.list_collection_names():
 				self.log.info(f"    ===> Collection: {i}")
-				for j in self.vision[i].find({"word_desc" : {"$regex" : keyword}}):
+				for j in self.vision[i].find({"word_desc" : re.compile(rf"\b{keyword}\b", re.IGNORECASE)}):
 					self.log.info(f"        ===> {j}")
 					data.append(j)
 		return data
@@ -299,7 +307,7 @@ def search_word_location(self, location):
 
 			for i in d.list_collection_names():
 				self.log.info(f"    ===> Collection: {i}")
-				for j in self.vision[i].find({"word_location" : {"$regex" : location}}):
+				for j in self.vision[i].find({"word_location" : re.compile(rf"\b{location}\b", re.IGNORECASE)}):
 					self.log.info(f"        ===> {j}")
 					data.append(j)
 		return data
@@ -320,8 +328,7 @@ def search_word_relation(self, relation):
 
 			for i in d.list_collection_names():
 				self.log.info(f"    ===> Collection: {i}")
-				for j in self.vision[i].find({"word_relation" : {"$regex" : relation}}):
+				for j in self.vision[i].find({"word_relation" : re.compile(rf"\b{relation}\b", re.IGNORECASE)}):
 					self.log.info(f"        ===> {j}")
 					data.append(j)
 		return data
-

src/MAGIST/TaskManagment/ThreadedQueue.py

@@ -7,6 +7,8 @@
 import threading
 import uuid
 import numpy as np
+import pathlib
+import json
 
 from ..Utils.LogMaster.log_init import MainLogger
 
@@ -27,6 +29,17 @@ def __init__(self, config):
 
 		self.function_returns = []
 
+		config = pathlib.Path(config)
+		config = config.resolve()  # Find absolute path from a relative one.
+		f = open(config)
+		config = json.load(f)
+
+		for i in config['task_management']:
+			try:
+				self.worker_threads = i["num_of_worker_threads"]
+			except KeyError:
+				pass
+
 	def __worker(self):
 		"""The worker thread. This actually executes the tasks in the queue.
 		"""
@@ -82,7 +95,8 @@ def detach_thread(self):
 		"""
 
 		# Turn-on the worker thread.
-		threading.Thread(target=self.__worker, daemon=True).start()
+		for i in range(self.worker_threads):
+			threading.Thread(target=self.__worker, daemon=True).start()
 		self.log.info("Thread created and daemonized. Queue started...")
 
 	def join_thread(self):

src/main.py

@@ -1,5 +1,6 @@
 from MAGIST.Vision.UnsupervisedModels.img_cluster import RoughCluster
 import time, os
+import numpy as np
 
 cluster = RoughCluster("config.json")
 
@@ -29,7 +30,7 @@ def dummy(a, b, c):
 	time.sleep(30)
 
 for l in labels:
-	queue.put_queue(dummy, l, 200, "Data/", name=f"Downloading {l}", priority=priority)
+	queue.put_queue(scraper.download_raw_img_dataset, l, 10, "Data/", name=f"Downloading {l}", priority=priority)
 	priority += 1
 
 
@@ -39,12 +40,12 @@ def dummy(a, b, c):
 
 
 
-for l in labels:
-	path = os.path.join("Data", l)
-	slicer.image_integrity_verification(path, delete_invalid=True)
-	slicer.resizer((500, 500), path)
-	coordinates = slicer.coordinate_compute((500, 500), (100, 100))
-	slicer.crop_segments(coordinates, path, "Sliced", l)
+# for l in labels:
+# 	path = os.path.join("Data", l)
+# 	slicer.image_integrity_verification(path, delete_invalid=True)
+# 	slicer.resizer((500, 500), path)
+# 	coordinates = slicer.coordinate_compute((500, 500), (100, 100))
+# 	slicer.crop_segments(coordinates, path, "Sliced", l)
 
 
 
@@ -53,7 +54,7 @@ def dummy(a, b, c):
 
 cnn = MAGIST_CNN("config.json")
 
-queue.put_queue(cnn, name="MAGIST_CNN_Trainer", priority=10)
+# queue.put_queue(cnn, name="MAGIST_CNN_Trainer", priority=10)
 
 from MAGIST.Utils.WebScraper.wikipedia import WikipediaScraper
 from MAGIST.NeuralDB.MongoUtils import AdminUtils
@@ -72,4 +73,30 @@ def dummy(a, b, c):
 	description = wiki.get_summary(l)
 	neural_db.insert_obj_desc(l, description)
 
-queue.join_thread()
+
+from MAGIST.NLP.AudioTranscriber import GoogleAudioTranscriber
+
+transcriber = GoogleAudioTranscriber("config.json")
+
+text = transcriber.microphone_listener()
+
+from MAGIST.NLP.SelfAttention import TextPreprocessing
+
+selfattention = TextPreprocessing("config.json")
+
+selected = []
+for i in selfattention.__call__(text):
+	if i[2] == "Good":
+		selected.append(i[1])
+
+
+search_res = []
+for i in selected:
+	res = neural_db.search_obj_details(i)
+	if res != []:
+		search_res.append(res)
+
+search_res = np.array(search_res)
+search_res = np.squeeze(search_res)
+
+print(search_res[0][3])