Add application file

app.py

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+import gradio as gr
+import torch
+import os
+import requests
+import json
+import cv2
+from PIL import Image
+from timeit import default_timer as timer
+import numpy as np
+import aiofiles
+from transformers import AutoModel
+
+model = torch.hub.load('ultralytics/yolov5','yolov5s', pretrained=True)
+#model1 = AutoModel.from_pretrained(model)
+cnt = 0
+def LCR(bbox,x_img, y_img):
+    x1 = bbox[0]/x_img
+    x2 = bbox[2]/x_img
+    if x1 < 0.2 and x2 < 0.2 :
+        location = "Left"
+    elif x1 > 0.8 and x2 > 0.8:
+        location = "Right"
+    elif x1 < 0.2 and (x2 <= 0.8 and x2 >= 0.2):
+        if (x1 + x2) < 0.4:
+            location = "Left"
+        else:
+            location = "Center" 
+    elif x2 > 0.8 and (x1 <= 0.8 and x1 >= 0.2):
+        if (x1 + x2) > 1.6:
+            location = "Right"
+        else:
+            location = "Center" 
+    else:
+        location = "Center"
+    print(f"x1 {x1} x2 {x2} bbox0 {bbox[0]} bbox2 {bbox[2]} x_img {x_img} LocationLCR {location}")
+    return location
+
+def ACB(bbox, x_img, y_img, location):
+    y1 = bbox[1]/y_img
+    y2 = bbox[3]/y_img
+    if location == "Center":
+        if y1 < 0.33333 and y2 < 0.33333 :
+            location = "Above"
+        elif y1 > 0.66667 and y2 > 0.66667:
+            location = "Below"
+        elif y1 < 0.33333 and (y2 <= 0.66667 and y2 >= 0.33333):
+            if (y1 + y2) < 0.66667:
+                location = "Above"
+            else:
+                location = "Center" 
+        elif y2 > 0.66667 and (y1 <= 0.66667 and y1 >= 0.33333):
+            if (y1 + y2) > 1.33333:
+                location = "Below"
+            else:
+                location = "Center" 
+        else:
+            location = "Center"
+    else:
+        pass
+    print(f"y1 {y1} y2 {y2} bbox1 {bbox[1]} bbox3 {bbox[3]} y_img {y_img} Location{location}")
+    
+    return location
+    #print(bbox[0])
+    
+def turn_img_into_fileJSON(frame):
+    start_time = timer()
+    x_img, y_img = frame.size
+    print(x_img,y_img)
+    global cnt
+    objects = []
+
+    prediction = model(frame)
+    for det in prediction.xyxy[0]:
+        class_id = int(det[5])
+        class_name = model.names[class_id]
+        confidence = float(det[4])
+        bbox = det[:4].tolist()
+        if(confidence >= 0.5):
+            location = LCR(bbox, x_img, y_img)
+            location = ACB(bbox, x_img, y_img, location)
+            # Save the results to the list
+            objects.append({
+                'Class': class_name,
+                #'BoundingBox': bbox,
+                'Location': location,
+                'Confidence': confidence
+            })
+        with open('{:05d}.json'.format(cnt)  , 'w') as f:
+            json.dump(objects, f)
+    cnt += 1
+    pred_time = round(timer() - start_time, 5)
+    json_str = json.dumps(objects)
+    return json_str, pred_time
+#path = [["D:/cuoc_thi/object-detection/download.jpg"],["C:/Users/ACER/Pictures/mydestiny/273536337_788402492117531_8798195010554693138_n.jpg"]]
+title = "Object-detection"
+description = "An EfficientNetB2 feature extractor computer vision model to classify images of object."
+article = "Created by Ryan"
+# Create the Gradio demo
+demo = gr.Interface(fn=turn_img_into_fileJSON, # mapping function from input to output
+                    inputs="pil", # what are the inputs?
+                    outputs=[gr.JSON(label="JSON Output"),
+                             #gr.Label(num_top_classes=80, label="Predictions"),
+                             gr.Number(label="Prediction time (s)")],
+                             #gr.outputs.Label(num_top_classes= 80),
+                    #examples=path, 
+                    title=title,
+                    description=description,
+                    article=article,
+                    live = True)
+#demo.launch()
+demo.launch(share=True)

requirements.txt

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+pybind11==2.11.1
+aiofiles==23.1.0
+aiohttp==3.8.5
+aiosignal==1.3.1
+altair==5.0.1
+annotated-types==0.5.0
+anyio==3.7.1
+async-timeout==4.0.2
+attrs==23.1.0
+charset-normalizer==3.2.0
+click==8.1.6
+colorama==0.4.6
+contourpy==1.1.0
+cycler==0.11.0
+exceptiongroup==1.1.2
+fastapi==0.100.1
+ffmpeg==1.4
+ffmpy==0.3.0
+filelock==3.12.2
+fonttools==4.41.1
+frozenlist==1.4.0
+fsspec==2023.6.0
+glog==0.3
+h11==0.14.0
+h2==4.1.0
+hpack==4.0.0
+httpcore==0.17.3
+httpx==0.24.1
+huggingface_hub==0.16.4
+hyperframe==6.0.1
+idna==3.4
+importlib-metadata==6.8.0
+importlib-resources==6.0.0
+importlib_metadata==6.8.0
+importlib_resources==6.0.0
+intel-openmp==2022.*
+jinja2==3.1.2
+joblib==1.3.0
+jsonschema==4.18.4
+jsonschema-specifications==2023.7.1
+kiwisolver==1.4.4
+libtiff==0.4.2
+linkify-it-py==2.0.0
+markdown-it-py==2.2.0
+markupsafe==2.1.3
+mdit-py-plugins==0.3.3
+mdurl==0.1.0
+mkl==2022.1.0
+multidict==6.0.4
+multiprocess==0.70.15
+munkres==1.1.4
+numpy==1.24.4
+orc==0.1.0
+orjson==3.9.2
+packaging==23.1
+pandas==2.0.3
+pillow==10.0.0
+pip==23.2.1
+pkgutil-resolve-name==1.3.10
+pyarrow==11.0.0
+pydantic==2.1.1
+pydantic-core==2.4.0
+pydub==0.25.1
+pyparsing==3.1.0
+pysocks==1.7.1
+python-dateutil==2.8.2
+python-multipart==0.0.6
+pytz==2023.3
+pyyaml==6.0
+re2==0.2.24
+referencing==0.30.0
+regex==2023.6.3
+requests==2.31.0
+rpds-py==0.9.2
+sacremoses==0.0.53
+safetensors==0.3.1
+semantic_version==2.10.0
+setuptools==68.0.0
+six==1.16.0
+snappy==3.1.1
+sniffio==1.3.0
+starlette==0.27.0
+tbb==2021.10.0
+tk==0.1.0
+tokenizers==0.13.3
+toolz==0.12.0
+tqdm==4.65.0
+transformers==4.31.0
+typing-extensions==4.7.1
+typing_extensions==4.7.1
+uc-micro-py==1.0.1
+unicodedata2==15.0.0
+urllib3==2.0.4
+uvicorn==0.23.1
+vc==2018.7.10
+websockets==11.0.3
+wheel==0.41.0
+win_inet_pton==1.1.0
+xxhash==3.2.0
+yarl==1.9.2
+zipp==3.16.2
+zstd==1.5.2
+asttokens==2.2.1
+backcall==0.2.0
+decorator==5.1.1
+executing==1.2.0
+gitdb==4.0.10
+gitpython==3.1.32
+gradio==3.39.0
+gradio-client==0.3.0
+ipython==8.12.2
+jedi==0.19.0
+matplotlib-inline==0.1.6
+mpmath==1.3.0
+networkx==3.1
+parso==0.8.3
+pickleshare==0.7.5
+prompt-toolkit==3.0.39
+psutil==5.9.5
+pure-eval==0.2.2
+pygments==2.15.1
+scipy==1.10.1
+seaborn==0.12.2
+smmap==5.0.0
+stack-data==0.6.2
+sympy==1.12
+torch==2.0.1
+torchvision==0.15.2
+traitlets==5.9.0
+wcwidth==0.2.6

yolov5s.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8b3b748c1e592ddd8868022e8732fde20025197328490623cc16c6f24d0782ee
+size 14808437