Spaces:
Runtime error
Runtime error
File size: 2,242 Bytes
d16b422 c96c440 d16b422 c96c440 d16b422 c96c440 d16b422 c96c440 d16b422 c96c440 d16b422 c96c440 d16b422 c96c440 d16b422 6989673 c96c440 6989673 d16b422 c96c440 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 |
import gradio as gr
import csv
import gemini
import base64
import httpx
# Load the protected-birds.txt file into a dictionary
protected_birds_dict = {}
with open('protected-birds.txt', 'r') as txtfile:
for line in txtfile:
bird, confidence = line.strip().split(',')
protected_birds_dict[bird.lower()] = float(confidence)
# Initialize the gemini client
def init_client(api_key):
return gemini.Client(api_key)
# Function to check if the feather is from a protected bird
def check_feather(image_url, api_key):
# Load the image
image_media_type = "image/jpeg"
image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")
# Make a prediction
client = init_client(api_key)
response = client.predict(
model_id="text-bison-001",
inputs={
"image": image_data,
"question": "Describe this image."
}
)
model_predictions = response["candidates"][0]["output"]
# Check if the feather is from a protected bird
protected = False
protected_birds_list = []
for bird, confidence in protected_birds_dict.items():
if bird in model_predictions.lower():
protected = True
protected_birds_list.append([bird, confidence, model_predictions])
if protected:
# Display the results
gr.Interface(fn=lambda: protected_birds_list, inputs="text", outputs="text").launch()
user_verification = gr.inputs.Checkbox(label="Verify the results")
if user_verification:
# Output the result in a table format
gr.Interface(fn=lambda: protected_birds_list, inputs=user_verification, outputs="html").launch()
# Prompt user to make a report
gr.Interface(fn=lambda: "If confident, report to: https://www.fws.gov/contact-us", inputs=user_verification, outputs="text").launch()
else:
gr.Interface(fn=lambda: "No protected bird detected", inputs=image_url, outputs="text").launch()
return protected, protected_birds_list
# Gradio interface
image_url = gr.inputs.Textbox()
api_key = gr.inputs.Textbox(label="Google API Key")
gr.Interface(fn=check_feather, inputs=[image_url, api_key], outputs="text").launch()
|