detr_hpc updated

detr_object_detection/detr_hpc/Dockerfile

@@ -17,22 +17,20 @@ ENV LOG_EVERY_N_STEP 5
 ENV MAX_NU_METRIC_IMAGES 10
 ENV DETECTION_THRESHOLD 0.8
 
-ENV GRPCPORT 8061
-ENV HTTPPORT 8062
-
-
 WORKDIR /home/objectdetection
 
 #RUN pip install --no-cache-dir jupyter
 
 COPY od ./od
 COPY __init__.py logger.py main.py config.py model_pb2_grpc.py model_pb2.py model.proto detr_server.py detr_client_test.py ./
-COPY cat1.png ./
+COPY app.py ./
+COPY static ./static
+COPY templates ./templates
 
 #EXPOSE 8061 8062
 
 
 ENTRYPOINT [ "python","main.py" ]
-#ENTRYPOINT jupyter notebook --ip=0.0.0.0 --port=8062 --allow-root --NotebookApp.token=''
+#python /home/objectdetection/main.py -gp 8061 -hp 8062 -f /p/home/jusers/hezarkhani1/juwels/testrun1 -d /p/home/jusers/hezarkhani1/judac/shared/maritimair
 
 

detr_object_detection/detr_hpc/app.py

-from flask import Flask, render_template, redirect, url_for, session, request
+from flask import Flask, render_template, redirect, url_for, session, request,Response
 from werkzeug.datastructures import MultiDict
 from flask_bootstrap import Bootstrap
 from flask_wtf import FlaskForm
@@ -8,13 +8,20 @@ from collections import namedtuple
 import os
 import json
 import copy
+import datetime, time
+
+import model_pb2
+import model_pb2_grpc
+import grpc
 
 from logger import Logger
 
 logger = Logger(__name__)
 
 config = None
-port = int(os.getenv("HTTPPORT", "8062"))
+httpport = None
+grpcport = None
+#port = int(os.getenv("HTTPPORT", "8062"))
 
 app = Flask(__name__)
 
@@ -87,6 +94,25 @@ class TrainingStatusForm(FlaskForm):
     TrainingStatus = StringField('Training status will be displayed here. Please save the parameters first before observing the status.', render_kw={'readonly': True})
     Get = SubmitField('Get Status')
 
+@app.route("/start_traing", methods=['POST'])
+def start_train():
+    logger.debug("Calling HPP_Stub for training")
+    addr = 'localhost:{}'.format(grpcport)
+    logger.debug("connecting to {}".format(addr))
+    with grpc.insecure_channel(addr) as channel:
+        stub = model_pb2_grpc.DetrModelServicerStub(channel)
+        
+        ui_request = model_pb2.TrainingConfig()
+        ui_request.config = "test"
+        response = stub.startTraining(ui_request)
+
+        logger.debug("Training finished")
+    
+    print(response)
+    return redirect('/')
+    
+
+
 
 @app.route('/', methods=['GET', 'POST'])
 def training_input():
@@ -127,11 +153,21 @@ def training_input():
     return render_template("index.html", training_var_form=training_vals_form, trainingStatusForm=trainingStatusForm, current_para=current_para)
 
 
-def app_run(config_main):
+# @app.route('/log')
+# def progress_log():
+# 	def generate():
+# 		for line in Pygtail(LOG_FILE, every_n=1):
+# 			yield "data:" + str(line) + "\n\n"
+# 			time.sleep(0.5)
+# 	return Response(generate(), mimetype= 'text/event-stream')
+
+def app_run(config_main,http_port_input,grpc_port_input):
     global config
+    global grpcport
+    grpcport = grpc_port_input
     config = config_main
     app.secret_key = "detr"
     bootstrap = Bootstrap(app)
-    app.run(host="0.0.0.0", port=port)
+    app.run(host="0.0.0.0", port=http_port_input)
 
 #app_run()
\ No newline at end of file

detr_object_detection/detr_hpc/config.py

 import os
 
 class Config:
-    def __init__(self, PROD_FLAG, SHARED_FOLDER):
+    def __init__(self, PROD_FLAG, SHARED_FOLDER, dataset_path = None):
         self.PROD_FLAG = PROD_FLAG
         self.SHARED_FOLDER = SHARED_FOLDER
 
@@ -34,7 +34,10 @@ class Config:
 
         self.TENSORBOARD_FOLDER = os.getenv(self.lightning_logs_dir, "./detr/dev/tensorboard_logs")
 
-        self.create_not_existing_dirs(([SHARED_FOLDER,self.custom_model_path,self.dataset_path,self.lightning_logs_dir,self.input_path,self.output_path,self.status_folder]))
+        self.create_not_existing_dirs([SHARED_FOLDER,self.custom_model_path,self.dataset_path,self.lightning_logs_dir,self.input_path,self.output_path,self.status_folder])
+
+        if dataset_path:
+            self.dataset_path = dataset_path
 
 
     def create_not_existing_dirs(self, list_of_paths):

detr_object_detection/detr_hpc/detr_client_test.py

@@ -41,14 +41,10 @@ def start_train():
     with grpc.insecure_channel(addr) as channel:
         stub = model_pb2_grpc.DetrModelServicerStub(channel)
         
-        #inference
         ui_request = model_pb2.TrainingConfig()
         ui_request.config = "test"
         response = stub.startTraining(ui_request)
 
-        # training
-        # ui_request = model_pb2.TrainingConfig(config="test")
-        # response = stub.startTraining(ui_request)
 
         logger.debug("Training finished")
     

detr_object_detection/detr_hpc/detr_server.py

@@ -9,7 +9,7 @@ import threading
 
 from od.detrOD import DetrOD
 from config import Config
-from app import app_run, get_train_parameters
+from app import get_train_parameters
 
 from logger import Logger
 logger = Logger(__name__)
@@ -160,18 +160,10 @@ class DetrModelServicer(model_pb2_grpc.DetrModelServicer):
             context.set_code(grpc.StatusCode.NOT_FOUND)
 
 
-def serve_grpc(config):
+def serve_grpc(config,port):
     server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
     model_pb2_grpc.add_DetrModelServicerServicer_to_server(DetrModelServicer(config), server)
     server.add_insecure_port('[::]:{}'.format(port))
     server.start()
     logger.info("Start config web-ui")
-    return server
-
-
-if __name__ == '__main__':
-    prod_flag = os.getenv("PRODUCTION", False)
-    config = Config(prod_flag, SHARED_FOLDER)
-    grpc_server = serve_grpc(config)
-    threading.Thread(target=app_run(config)).start()
-    grpc_server.wait_for_termination()
\ No newline at end of file
+    return server
\ No newline at end of file

detr_object_detection/detr_hpc/main.py

@@ -2,20 +2,27 @@ from od.detrOD import DetrOD
 import os 
 from config import Config
 import detr_server
-
+from app import app_run
 import argparse
-parser = argparse.ArgumentParser(description='Process some integers.')
-parser.add_argument('-i','--input', type=str , help='Input Image',required=True) # will be accesible with args.OPT
-parser.add_argument('-o','--output', type=str , help='Output Image',required=True) # will be accesible with args.OPT
-parser.add_argument('-f','--folder', type=str , help='Path for files directory',required=True) # will be accesible with args.OPT
-
-args = parser.parse_args()
+import threading
 
 if __name__ == '__main__':
-    folder_path = args.folder
+    parser = argparse.ArgumentParser(description='Process some integers.')
+    parser.add_argument('-gp','--grpc-port', type=int , help='grpc port',required=True)
+    parser.add_argument('-hp','--http-port', type=int , help='http port',required=True) 
+    parser.add_argument('-f','--folder', type=str , help='Folder path',required=True) 
+    parser.add_argument('-d','--dataset-path', type=str , help='Dataset path',required=True) 
+
+    args = parser.parse_args()
+
+    # run_inference(args.input, args.output)
+
     prod_flag = os.getenv("PRODUCTION", False)
-    config = Config(prod_flag,folder_path)
-    detr_server.serve(config)
+    config = Config(prod_flag, args.folder, args.dataset_path)
+    grpc_server = detr_server.serve_grpc(config, args.grpc_port)
+    #threading.Thread(target=app_run(config,args.http_port,args.grpc_port)).start()
+    threading.Thread(target=app_run, args=(config, args.http_port, args.grpc_port)).start()
+    grpc_server.wait_for_termination()
 
 # detrOd = DetrOD(config)
 # input_image = args.input

detr_object_detection/detr_hpc/od/detrOD.py

@@ -70,10 +70,10 @@ class DetrOD():
               dataloader_workers:int = 0
               ):
         logger.info("Training batch size is {}".format(batch_size))
-        
         logger.info("Using databasee under this path for training: {}".format(self.config.dataset_path))
         logger.info("Trained model will be saved in this path: {}".format(self.config.custom_model_path))
 
+        
         dataprovider = DataProvider(extractor=self.extractor, 
                                     dataset_path=self.config.dataset_path, 
                                     annotation_file_name=self.config.annotation_file_name, 
@@ -131,6 +131,7 @@ class DetrOD():
 
 
     def get_metrics(self,threshold=0.7):
+
         logger.info("Getting metrics with current threshhold of: {}".format(threshold))
         preds = []
         target = []

detr_object_detection/detr_hpc/static/js/scripts.js

+$(document).ready(function(){
+    $('#startBtn').click(function(){
+        console.log("submit recieved")
+        $.ajax({
+            type: 'POST',
+            url: '/start_traing',
+            contentType: 'application/json',
+            success: function(response){
+                console.log(response);
+                alert(response.message);
+            },
+            error: function(xhr, status, error){
+                console.error(error);
+                alert('An error occurred while sending the request.');
+            }
+        });
+    });
+});
\ No newline at end of file

detr_object_detection/detr_hpc/templates/index.html

@@ -16,9 +16,8 @@
         <div class="card-body">
           {{ render_form(training_var_form) }}
         </div>
+        
       </div>
-      
-
     </div>
     <div class="col-6 mb-4">
       <div class="card shadow mb-4">
@@ -38,9 +37,25 @@
           <textarea class="form-control" style="height:100%;">{{ current_para }}</textarea>
         </div>
       </div>
+
+
+      
     </div>
 
     
+  </div>
+  <div class="row">
+    <div class="col-12 mb-4">
+      <div class="card shadow mb-4">
+        
+        <div class="card-body">
+          <button type="button" id="startBtn" class="btn btn-warning btn-block">Start Training</button>
+        </div>
+        
+      </div>
+      
+    </div>
+    
   </div>
 </div>
 
@@ -54,5 +69,6 @@
 
 <!-- Custom scripts for all pages-->
 <script src="static/js/sb-admin-2.min.js"></script>
+<script src="static/js/scripts.js"></script>
 
 </body>
\ No newline at end of file