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import gradio as gr
import cv2
from gradio_webrtc import WebRTC
import os
# import mediapipe as mp
# from mediapipe.tasks import python
# from mediapipe.tasks.python import vision, BaseOptions
# from mediapipe import solutions
# from mediapipe.framework.formats import landmark_pb2
import numpy as np
import cv2
from PIL import Image
MODEL_PATH = r"pose_landmarker_lite.task"
# Drawing landmarks
# def draw_landmarks_on_image(rgb_image, detection_result):
# pose_landmarks_list = detection_result.pose_landmarks
# annotated_image = np.copy(rgb_image)
# for pose_landmarks in pose_landmarks_list:
# pose_landmarks_proto = landmark_pb2.NormalizedLandmarkList()
# pose_landmarks_proto.landmark.extend([
# landmark_pb2.NormalizedLandmark(x=landmark.x, y=landmark.y, z=landmark.z) for landmark in pose_landmarks
# ])
# solutions.drawing_utils.draw_landmarks(
# annotated_image,
# pose_landmarks_proto,
# solutions.pose.POSE_CONNECTIONS,
# solutions.drawing_styles.get_default_pose_landmarks_style())
# return annotated_image
# base_options = python.BaseOptions(delegate=0,model_asset_path=MODEL_PATH)
# options = vision.PoseLandmarkerOptions(
# base_options=base_options,
# output_segmentation_masks=True)
# detector = vision.PoseLandmarker.create_from_options(options)
def detection(image, conf_threshold=0.3):
frame = cv2.flip(image, 1)
rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
rgb_frame=cv2.circle(rgb_frame,(90,90),(255,0,0),20)
# mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=rgb_frame)
# # Pose detection
# detection_result = detector.detect(mp_image)
# # Draw landmarks
# annotated_image = draw_landmarks_on_image(mp_image.numpy_view(), detection_result)
return rgb_frame
with gr.Blocks() as demo:
image = WebRTC(label="Stream", mode="send-receive", modality="video", height=480, width=640, mirror_webcam=True)
conf_threshold = gr.Slider(
label="Confidence Threshold",
minimum=0.0,
maximum=1.0,
step=0.05,
value=0.30,
)
image.stream(
fn=detection,
inputs=[image, conf_threshold],
outputs=[image]
)
if __name__ == "__app__":
demo.launch(share=True)
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