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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,157 +1,161 @@ | ||
| import cv2 | ||
| import time | ||
| import numpy as np | ||
| import psutil | ||
| import sys | ||
| import os | ||
| import pathlib | ||
| from datetime import datetime | ||
|
|
||
| def collectdataset(rtsp, names_file, weight_file, cfg_file, path, dir_n, x_1, y_1, w_1, z_1, poly, roi, pts_left, pts_right,cnf=0.6,exit_percent=200.0): | ||
| print("inside the function") | ||
| CONFIDENCE_THRESHOLD = cnf | ||
| NMS_THRESHOLD = 0.1 | ||
|
|
||
| def get_video_capture(rtsp_url): | ||
| cap = cv2.VideoCapture(rtsp_url, cv2.CAP_FFMPEG) | ||
| if not cap.isOpened(): | ||
| print("Failed to open the stream.") | ||
| return None | ||
| return cap | ||
|
|
||
| cap = cv2.VideoCapture(rtsp, cv2.CAP_FFMPEG) | ||
| # cap = get_video_capture(rtsp) | ||
| class_names = [] | ||
| with open(names_file, "r") as f: | ||
| class_names = [cname.strip() for cname in f.readlines()] | ||
|
|
||
| net = cv2.dnn.readNet(weight_file, cfg_file) | ||
| model = cv2.dnn_DetectionModel(net) | ||
| model.setInputParams(size=(640, 640), scale=1/255, swapRB=True) | ||
| pathlib.Path(path + str(dir_n)).mkdir(parents=True, exist_ok=True) | ||
| try: | ||
| while True: | ||
| if cap is not None: | ||
| cpu_percent = psutil.cpu_percent(interval=1) | ||
| while cpu_percent > exit_percent: | ||
| print(f"CPU utilization: {cpu_percent}%") | ||
| print(f"CPU utilization exceeded {exit_percent}%. Pausing until CPU utilization decreases...") | ||
| time.sleep(5) # Sleep for 5 seconds before checking again | ||
| cpu_percent = psutil.cpu_percent(interval=1) | ||
| print(f"CPU utilization: {cpu_percent}%") | ||
| print(f"CPU utilization: {cpu_percent}%") | ||
| ret, frame = cap.read() | ||
| if ret: | ||
| if poly: | ||
| frame_crop = frame.copy() | ||
| cv2.fillPoly(frame_crop, [pts_left], 0) | ||
| cv2.fillPoly(frame_crop, [pts_right], 0) | ||
| elif roi: | ||
| frame_crop = frame[y_1:z_1, x_1:w_1] | ||
| else: | ||
| frame_crop = frame | ||
| frame_crop = np.array(frame_crop) | ||
| frame = np.array(frame) | ||
| start=time.time() | ||
| classes, scores, boxes = model.detect(frame_crop, CONFIDENCE_THRESHOLD, NMS_THRESHOLD) | ||
| end=time.time() | ||
| print("Time taken for inference : ",end-start) | ||
| for (classid, score, box) in zip(classes, scores, boxes): | ||
| print(class_names[classid], score) | ||
| print("found!!!") | ||
| curr_datetime = datetime.utcnow().strftime('%Y%m%d%H%M%S%f') | ||
| f_name = path + dir_n + "/" + str(curr_datetime) + ".jpg" | ||
| cv2.imwrite(f_name, frame) | ||
| print(f_name) | ||
| else: | ||
| print("No Frame, attempting to reconnect...") | ||
| cap.release() | ||
| time.sleep(3) # Wait for 5 seconds before trying to reconnect | ||
| cap = get_video_capture(rtsp) | ||
| else: | ||
| # Attempt to reconnect if the capture is None | ||
| print("Error in frame") | ||
| time.sleep(3) | ||
| cap = get_video_capture(rtsp) | ||
|
|
||
| if cap is not None: | ||
| cap.release() | ||
|
|
||
|
|
||
| except KeyboardInterrupt: | ||
| print("Bye") | ||
| sys.exit() | ||
|
|
||
| # import cv2 | ||
| # import time | ||
| # import numpy as np | ||
| # import psutil | ||
| # import sys | ||
| # import os | ||
| # import pathlib | ||
| # import time | ||
| # from datetime import datetime | ||
| # import sys | ||
| # CONFIDENCE_THRESHOLD = 0.7 | ||
| # NMS_THRESHOLD = 0.1 | ||
|
|
||
|
|
||
| # def collectdataset(rtsp, names_file, weight_file, cfg_file, path, dir_n, x_1, y_1, w_1, z_1, poly, roi, pts_left, pts_right,cnf=0.6,exit_percent=200.0): | ||
| # def collectdataset(rtsp,names_file,weight_file,cfg_file,path,dir_n,x_1,y_1,w_1,z_1,poly,roi,pts_left,pts_right,exit_percent=200.0): | ||
| # print("inside the function") | ||
| # CONFIDENCE_THRESHOLD = cnf | ||
| # NMS_THRESHOLD = 0.1 | ||
|
|
||
| # def get_video_capture(rtsp_url): | ||
| # cap = cv2.VideoCapture(rtsp_url, cv2.CAP_FFMPEG) | ||
| # if not cap.isOpened(): | ||
| # print("Failed to open the stream.") | ||
| # return None | ||
| # return cap | ||
|
|
||
| # cap = cv2.VideoCapture(rtsp, cv2.CAP_FFMPEG) | ||
| # # cap = get_video_capture(rtsp) | ||
| # prevTime = 0 | ||
| # # width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) | ||
| # # height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) | ||
| # #cv2.namedWindow("output", cv2.WINDOW_NORMAL) | ||
| # class_names = [] | ||
| # with open(names_file, "r") as f: | ||
| # class_names = [cname.strip() for cname in f.readlines()] | ||
|
|
||
| # net = cv2.dnn.readNet(weight_file, cfg_file) | ||
|
|
||
| # # frame_width = int(cap.get(3)) | ||
| # # frame_height = int(cap.get(4)) | ||
| # # size = (frame_width, frame_height) | ||
| # #colors = np.random.uniform(0,255,size=(len(class_names),3)) | ||
| # net = cv2.dnn.readNet(weight_file,cfg_file) | ||
| # model = cv2.dnn_DetectionModel(net) | ||
| # model.setInputParams(size=(640, 640), scale=1/255, swapRB=True) | ||
| # pathlib.Path(path + str(dir_n)).mkdir(parents=True, exist_ok=True) | ||
| # pathlib.Path(path+str(dir_n)).mkdir(parents=True, exist_ok=True) | ||
| # print("Is rtsp stream opend :",cap.isOpened()) | ||
| # try: | ||
| # while True: | ||
| # if cap is not None: | ||
| # while cap.isOpened(): | ||
| # cpu_percent = psutil.cpu_percent(interval=1) | ||
| # while cpu_percent > exit_percent: | ||
| # print(f"CPU utilization: {cpu_percent}%") | ||
| # print(f"CPU utilization exceeded {exit_percent}%. Pausing until CPU utilization decreases...") | ||
| # print("sleeping for 5 seconds") | ||
| # time.sleep(5) # Sleep for 1 second before checking again | ||
| # cpu_percent = psutil.cpu_percent(interval=1) | ||
| # while cpu_percent > exit_percent: | ||
| # print(f"CPU utilization: {cpu_percent}%") | ||
| # print(f"CPU utilization exceeded {exit_percent}%. Pausing until CPU utilization decreases...") | ||
| # time.sleep(5) # Sleep for 5 seconds before checking again | ||
| # cpu_percent = psutil.cpu_percent(interval=1) | ||
|
|
||
| # ret, frame = cap.read() | ||
| # if ret: | ||
| # if poly: | ||
| # frame_crop = frame.copy() | ||
| # cv2.fillPoly(frame_crop, [pts_left], 0) | ||
| # cv2.fillPoly(frame_crop, [pts_right], 0) | ||
| # elif roi: | ||
| # frame_crop = frame[y_1:z_1, x_1:w_1] | ||
| # else: | ||
| # frame_crop = frame | ||
| # frame_crop = np.array(frame_crop) | ||
| # frame = np.array(frame) | ||
| # classes, scores, boxes = model.detect(frame_crop, CONFIDENCE_THRESHOLD, NMS_THRESHOLD) | ||
| # for (classid, score, box) in zip(classes, scores, boxes): | ||
| # print(class_names[classid], score) | ||
| # print(f"CPU utilization: {cpu_percent}%") | ||
| # print(f"CPU utilization: {cpu_percent}%") | ||
| # ret, frame = cap.read() | ||
| # if ret: | ||
| # #frame=cv2.resize(frame, (900, 900)) | ||
| # if poly: | ||
| # frame_crop=frame.copy() | ||
| # cv2.fillPoly(frame_crop, [pts_left], 0) | ||
| # cv2.fillPoly(frame_crop, [pts_right], 0) | ||
| # elif roi: | ||
| # frame_crop=frame[y_1:z_1,x_1:w_1] | ||
| # else: | ||
| # frame_crop=frame | ||
| # frame_crop= np.array(frame_crop) | ||
| # # frame=cv2.resize(frame, (900, 900)) | ||
| # frame = np.array(frame) | ||
| # start=time.time() | ||
| # classes, scores, boxes = model.detect(frame_crop, CONFIDENCE_THRESHOLD, NMS_THRESHOLD) | ||
| # end=time.time() | ||
| # print("Time taken for inference : ",end-start) | ||
| # for (classid, score, box) in zip(classes, scores, boxes): | ||
| # print(class_names[classid],score) | ||
| # print("found!!!") | ||
| # curr_datetime = datetime.utcnow().strftime('%Y%m%d%H%M%S%f') | ||
| # f_name = path + dir_n + "/" + str(curr_datetime) + ".jpg" | ||
| # f_name = path+dir_n+"/"+str(curr_datetime)+".jpg" | ||
| # cv2.imwrite(f_name, frame) | ||
| # print(f_name) | ||
| # else: | ||
| # print("No Frame, attempting to reconnect...") | ||
| # cap.release() | ||
| # time.sleep(5) # Wait for 5 seconds before trying to reconnect | ||
| # cap = get_video_capture(rtsp) | ||
| # else: | ||
| # # Attempt to reconnect if the capture is None | ||
| # print("Error in frame") | ||
| # time.sleep(3) | ||
| # cap = get_video_capture(rtsp) | ||
|
|
||
| # if cap is not None: | ||
| # cap.release() | ||
|
|
||
|
|
||
| # print("No Frame") | ||
| # except KeyboardInterrupt: | ||
| # print("Bye") | ||
| # sys.exit() | ||
|
|
||
| import cv2 | ||
| import time | ||
| import numpy as np | ||
| import psutil | ||
| import sys | ||
| import os | ||
| import pathlib | ||
| import time | ||
| from datetime import datetime | ||
| import sys | ||
| CONFIDENCE_THRESHOLD = 0.7 | ||
| NMS_THRESHOLD = 0.1 | ||
|
|
||
|
|
||
| def collectdataset(rtsp,names_file,weight_file,cfg_file,path,dir_n,x_1,y_1,w_1,z_1,poly,roi,pts_left,pts_right,exit_percent=200.0): | ||
| print("inside the function") | ||
| cap = cv2.VideoCapture(rtsp, cv2.CAP_FFMPEG) | ||
| prevTime = 0 | ||
| # width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) | ||
| # height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) | ||
| #cv2.namedWindow("output", cv2.WINDOW_NORMAL) | ||
| class_names = [] | ||
| with open(names_file, "r") as f: | ||
| class_names = [cname.strip() for cname in f.readlines()] | ||
|
|
||
|
|
||
| # frame_width = int(cap.get(3)) | ||
| # frame_height = int(cap.get(4)) | ||
| # size = (frame_width, frame_height) | ||
| #colors = np.random.uniform(0,255,size=(len(class_names),3)) | ||
| net = cv2.dnn.readNet(weight_file,cfg_file) | ||
| model = cv2.dnn_DetectionModel(net) | ||
| model.setInputParams(size=(640, 640), scale=1/255, swapRB=True) | ||
| pathlib.Path(path+str(dir_n)).mkdir(parents=True, exist_ok=True) | ||
| print("Is rtsp stream opend :",cap.isOpened()) | ||
| try: | ||
| while cap.isOpened(): | ||
| cpu_percent = psutil.cpu_percent(interval=1) | ||
| while cpu_percent > exit_percent: | ||
| print(f"CPU utilization: {cpu_percent}%") | ||
| print(f"CPU utilization exceeded {exit_percent}%. Pausing until CPU utilization decreases...") | ||
| print("sleeping for 5 seconds") | ||
| time.sleep(5) # Sleep for 1 second before checking again | ||
| cpu_percent = psutil.cpu_percent(interval=1) | ||
|
|
||
| print(f"CPU utilization: {cpu_percent}%") | ||
| print(f"CPU utilization: {cpu_percent}%") | ||
| ret, frame = cap.read() | ||
| if ret: | ||
| #frame=cv2.resize(frame, (900, 900)) | ||
| if poly: | ||
| frame_crop=frame.copy() | ||
| cv2.fillPoly(frame_crop, [pts_left], 0) | ||
| cv2.fillPoly(frame_crop, [pts_right], 0) | ||
| elif roi: | ||
| frame_crop=frame[y_1:z_1,x_1:w_1] | ||
| else: | ||
| frame_crop=frame | ||
| frame_crop= np.array(frame_crop) | ||
| # frame=cv2.resize(frame, (900, 900)) | ||
| frame = np.array(frame) | ||
| start=time.time() | ||
| classes, scores, boxes = model.detect(frame_crop, CONFIDENCE_THRESHOLD, NMS_THRESHOLD) | ||
| end=time.time() | ||
| print("Time taken for inference : ",end-start) | ||
| for (classid, score, box) in zip(classes, scores, boxes): | ||
| print(class_names[classid],score) | ||
| print("found!!!") | ||
| curr_datetime = datetime.utcnow().strftime('%Y%m%d%H%M%S%f') | ||
| f_name = path+dir_n+"/"+str(curr_datetime)+".jpg" | ||
| cv2.imwrite(f_name, frame) | ||
| print(f_name) | ||
| else: | ||
| print("No Frame") | ||
| except KeyboardInterrupt: | ||
| print("Bye") | ||
| sys.exit() |