Create app.py

app.py

@@ -0,0 +1,168 @@
+import requests
+import numpy as np
+import gradio as gr
+import io
+import matplotlib.pyplot as plt
+from PIL import Image, ImageDraw, ImageFont
+
+def send2api(input_img, api_url):
+    buf = io.BytesIO()
+    plt.imsave(buf, input_img, format='jpg')
+    files = {'image': buf.getvalue()}
+    res = requests.post(api_url, files=files)
+    try:
+        res.raise_for_status()
+        if res.status_code != 204:
+            response = res.json()
+    except Exception as e:
+        print(str(e))
+    return response
+
+def display_detectionsandcountings_detclasim(img_array, detections, c_cnames, c_scinames, coverage, prob_th=0, cth = 0):
+    img = Image.fromarray(img_array)
+    img1 = ImageDraw.Draw(img)
+    h, w = img.size
+    ratio = h/4000
+
+    for (box, _, y_prob, y_class, sciname) in detections:
+        y_prob = float(y_prob)
+        if y_prob > prob_th:
+            img1.rectangle(box, outline='red', width=int(20*ratio))
+            img1.text(box[:2], y_class+str(round(y_prob,3)), fill='white')
+
+    countings_list = list(c_scinames.items())
+    countings_list.sort(key = lambda x: x[1], reverse=True)
+    yi=int(20*ratio)
+    total = 0
+    for (y_class,c) in countings_list:
+        if c > cth:
+            img1.text((int(50*ratio), yi), "# {} = {}".format(y_class, c), fill='red')
+            yi += int(100*ratio)
+            total += c
+    yi += int(100*ratio)
+    img1.text((int(50*ratio), yi), "# {} = {}".format('total', total), fill='red')
+
+    text = f'coverage = {coverage}'+'\n\n'
+    text += 'Countings by scientific name:\n'
+    countings_list = list(c_scinames.items())
+    countings_list.sort(key = lambda x: x[1], reverse=True)
+    for key,value in countings_list:
+      text += f'{key} = {value}'+'\n'
+    text += '\n\n'
+    text += 'Countings by common name:\n'
+
+    countings_list = list(c_cnames.items())
+    countings_list.sort(key = lambda x: x[1], reverse=True)
+    for key,value in countings_list:
+      text += f'{key} = {value}'+'\n'
+    text += '\n'
+    text += f'total = {total}'+'\n'
+    return img, text
+
+def display_detectionsandcountings_yolocounter(img_array, detections, countings, coverage, prob_th=0, cth = 0):
+    img = Image.fromarray(img_array)
+    img1 = ImageDraw.Draw(img)
+    h, w = img.size
+    ratio = h/4000
+
+    for (box, _, y_prob, y_class) in detections:
+        y_prob = float(y_prob)
+        if y_prob > prob_th:
+            img1.rectangle(box, outline='red', width=int(20*ratio))
+            img1.text(box[:2], y_class+str(round(y_prob,3)), fill='white')
+
+    countings_list = list(countings.items())
+    countings_list.sort(key = lambda x: x[1], reverse=True)
+    yi=int(20*ratio)
+    total = 0
+    for (y_class,c) in countings_list:
+        if c > cth:
+            img1.text((int(50*ratio), yi), "# {} = {}".format(y_class, c), fill='red')
+            yi += int(100*ratio)
+            total += c
+    yi += int(100*ratio)
+    img1.text((int(50*ratio), yi), "# {} = {}".format('total', total), fill='red')
+
+    text = f'coverage = {coverage}'+'\n\n'
+    for key,value in countings_list:
+        text += f'{key} = {value}'+'\n'
+    text += '\n'
+    text += f'total = {total}'+'\n'
+    return img, text
+
+def display_detectionsandcountings_directcounter(img_array, countings, prob_th=0, cth = 0):
+    img = Image.fromarray(img_array)
+    img1 = ImageDraw.Draw(img)
+    h, w = img.size
+    ratio = h/4000
+
+    countings_list = list(countings.items())
+    countings_list.sort(key = lambda x: x[1], reverse=True)
+    yi=int(20*ratio)
+    total = 0
+    for (y_class,c) in countings_list:
+        if c > cth:
+            img1.text((int(50*ratio), yi), "# {} = {}".format(y_class, c), fill='red')
+            yi += int(100*ratio)
+            total += c
+    yi += int(100*ratio)
+    img1.text((int(50*ratio), yi), "# {} = {}".format('total', total), fill='red')
+
+    text = ''
+    for key,value in countings_list:
+        text += f'{key} = {value}'+'\n'
+    text += '\n'
+    text += f'total = {total}'+'\n'
+    return img, text
+
+def testing_countingid(input_img):
+    api_url = 'http://countingid-test.us-east-1.elasticbeanstalk.com/predict'
+    response = send2api(input_img, api_url)
+    c_cnames = response['countings_cnames']
+    c_scinames = response['countings_scinames']
+    coverage = response['coverage']
+    detections = response['detections']
+    img, text = display_detectionsandcountings_detclasim(input_img, detections, c_cnames, c_scinames, coverage, prob_th=0, cth = 0)
+    return img, text
+
+def testing_yolocounter(input_img):
+    api_url = 'http://yolocounter-test.us-east-1.elasticbeanstalk.com/predict'
+    response = send2api(input_img, api_url)
+    countings = response['countings_scinames']
+    coverage = response['coverage']
+    detections = response['detections']
+    img, text = display_detectionsandcountings_yolocounter(input_img, detections, countings, coverage, prob_th=0, cth = 0)
+    return img, text
+
+def testing_directcounter(input_img):
+    api_url = 'http://directcounter-test.us-east-1.elasticbeanstalk.com/predict'
+    response = send2api(input_img, api_url)
+    countings = response['countings_scinames']
+    img, text = display_detectionsandcountings_directcounter(input_img, countings, prob_th=0, cth = 0)
+    return img, text
+
+with gr.Blocks() as demo:
+    gr.Markdown("Submit an image with insects in a trap")
+
+    with gr.Tab("DetClaSim-based insect counter"):
+        with gr.Row():
+            input1 = gr.Image(shape=(500,500))
+            output1 =[gr.Image().style(height=500, width=500), gr.Textbox(lines=20)]
+        button1 = gr.Button("Submit")
+    button1.click(testing_countingid, input1, output1)
+
+    with gr.Tab("Yolocounter-based insect counter"):
+        with gr.Row():
+            input2 = gr.Image(shape=(500,500))
+            output2 =[gr.Image().style(height=500, width=500), gr.Textbox(lines=20)]
+        button2 = gr.Button("Submit")
+    button2.click(testing_yolocounter, input2, output2)
+
+    with gr.Tab("Direct insect counter"):
+        with gr.Row():
+            input3 = gr.Image(shape=(500,500))
+            output3 =[gr.Image().style(height=500, width=500), gr.Textbox(lines=20)]
+        button3 = gr.Button("Submit")
+    button3.click(testing_directcounter, input3, output3)
+
+demo.launch(share=True)