import torch
import cv2
import numpy as np
import gradio as gr


model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)


model.conf = 0.25  
model.iou = 0.45  
model.agnostic = False  
model.multi_label = False  
model.max_det = 1000


def detect(img):


    results = model(img, size=640)

    predictions = results.pred[0]
    boxes = predictions[:, :4] # x1, y1, x2, y2
    scores = predictions[:, 4]
    categories = predictions[:, 5]
    dfResults = results.pandas().xyxy[0]
    return drawRectangles(image, dfResults[['xmin', 'ymin', 'xmax','ymax']].astype(int))

def drawRectangles(image, dfResults):
    for index, row in dfResults.iterrows():
      print( (row['xmin'], row['ymin']))
      image = cv2.rectangle(image, (row['xmin'], row['ymin']), (row['xmax'], row['ymax']), (255, 0, 0), 2)
    return image    


img = gr.inputs.Image(shape=(192, 192))

intf = gr.Interface(fn=detect, inputs=img, outputs='image')
intf.launch(inline=False)