<p>I am using this git package to run target detection using YOLOv4 in Python</p> <pre class="brush:php;toolbar:false;">https://github.com/erentknn/yolov4-object-detection</pre> <p>The script runs fine and I can print out the found targets in the terminal with confidence, but when I execute it from PHP the results returned are empty. I guess it might be because the PHP script is waiting for Python to finish and not returning the results in real time. I tried creating a dictionary to store the results and return it at the end, but it still returns empty. I used to be able to do this easily in YOLOv3, not sure what has changed in v4. </p> <p>Edit: After more testing, I can't even write the results to a file, which is weird. If run from terminal I can. </p> <p>EDIT: If I var_dump($output), it returns NULL. After turning on debugging, no additional information is returned.</p> <p>我正在运行脚本 - yolo_video.py</p> <pre class="brush:php;toolbar:false;"># example usage: python3 yolo_video.py -i video.mp4 -o video_out.avi import argparse import glob import time import logging from pathlib import Path import cv2 import numpy as np logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) formatter = logging.Formatter("%(asctime)s-%(name)s-%(message)s") stream_handler = logging.StreamHandler() stream_handler.setFormatter(formatter) logger.addHandler(stream_handler) parser = argparse.ArgumentParser() parser.add_argument("-i", "--input", type=str, default="", help="video.mp4") parser.add_argument("-o", "--output", type=str, default="", help="path to (optional) output video file") parser.add_argument("-d", "--display", type=int, default=1, help="display output or not (1/0)") parser.add_argument("-ht", "--height", type=int, default=1200, help="height of output") parser.add_argument("-wt", "--width", type=int, default=700, help="width of output") parser.add_argument("-c", "--confidence", type=float, default=0.8, help="confidence threshold") parser.add_argument("-t", "--threshold", type=float, default=0.6, help="non-maximum supression threshold") args = parser.parse_args() logger.info("Parsed Arguments") CONFIDENCE_THRESHOLD = args.confidence NMS_THRESHOLD = args.threshold if not Path(args.input).exists(): raise FileNotFoundError("Path to video file is not exist.") vc = cv2.VideoCapture(args.input) weights = glob.glob("yolo/*.weights")[0] labels = glob.glob("yolo/*.txt")[0] cfg = glob.glob("yolo/*.cfg")[0] logger.info("Using {} weights ,{} configs and {}labels.".format(weights, cfg, labels)) class_names = list() with open(labels, "r") as f: class_names = [cname.strip() for cname in f.readlines()] COLORS = np.random.randint(0, 255, size=(len(class_names), 3), dtype="uint8") net = cv2.dnn.readNetFromDarknet(cfg, weights) net.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA) net.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA) layer = net.getLayerNames() layer = [layer[i[0] - 1] for i in net.getUnconnectedOutLayers()] writer = None def detect(frm, net, ln): (H, W) = frm.shape[:2] blob = cv2.dnn.blobFromImage(frm, 1 / 255.0, (416, 416), swapRB=True, crop=False) net.setInput(blob) start_time = time.time() layerOutputs = net.forward(ln) end_time = time.time() boxes = [] classIds = [] confidences = [] for output in layerOutputs: for detection in output: scores = detection[5:] classID = np.argmax(scores) confidence = scores[classID] if confidence > CONFIDENCE_THRESHOLD: box = detection[0:4] * np.array([W, H, W, H]) (centerX, centerY, width, height) = box.astype("int") x = int(centerX - (width / 2)) y = int(centerY - (height / 2)) boxes.append([x, y, int(width), int(height)]) classIds.append(classID) confidences.append(float(confidence)) idxs = cv2.dnn.NMSBoxes(boxes, confidences, CONFIDENCE_THRESHOLD, NMS_THRESHOLD) if len(idxs) > 0: for i in idxs.flatten(): (x, y) = (boxes[i][0], boxes[i][1]) (w, h) = (boxes[i][2], boxes[i][3]) color = [int(c) for c in COLORS[classIds[i]]] cv2.rectangle(frm, (x, y), (x w, y h), color, 2) text = "{}: {:.4f}".format(class_names[classIds[i]], confidences[i]) # Here I print the results (working in terminal) print("found") print(confidences[i]) print(class_names[classIds[i]]) cv2.putText( frm, text, (x, y - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 2 ) fps_label = "FPS: %.2f" % (1 / (end_time - start_time)) cv2.putText( frm, fps_label, (0, 25), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2 ) while cv2.waitKey(1) < 1: (grabbed, frame) = vc.read() if not grabbed: break frame = cv2.resize(frame, (args.height, args.width)) detect(frame, net, layer) if writer is not None: writer.write(frame)</pre> <p>Then in my PHP script</p> <pre class="brush:php;toolbar:false;">$command = escapeshellcmd('python3 yolo_video.py -i video.mp4 -o video_out.avi'); $output = shell_exec($command); echo $output;</pre> <p>How to output the results of Python script in PHP? I don't get any errors and the script completes. </p>

while(vc.isOpened()):

if frame is None:
        break

if not grabbed:
        break